Overview

Brought to you by YData

Dataset statistics

Number of variables	23
Number of observations	49866
Missing cells	274607
Missing cells (%)	23.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	8.4 MiB
Average record size in memory	177.0 B

Variable types

Text	14
Numeric	6
Categorical	2
DateTime	1

Alerts

`final_budget` is highly overall correlated with `final_domestic_boxoffice` and 1 other fields	High correlation
`final_domestic_boxoffice` is highly overall correlated with `final_budget` and 1 other fields	High correlation
`final_worldwide_boxoffice` is highly overall correlated with `final_budget` and 1 other fields	High correlation
`_merge` is highly imbalanced (57.0%)	Imbalance
`final_budget` has 36038 (72.3%) missing values	Missing
`final_worldwide_boxoffice` has 37177 (74.6%) missing values	Missing
`final_domestic_boxoffice` has 34819 (69.8%) missing values	Missing
`final_genres` has 3706 (7.4%) missing values	Missing
`final_runtime` has 5534 (11.1%) missing values	Missing
`final_overview` has 5196 (10.4%) missing values	Missing
`final_certificate` has 27216 (54.6%) missing values	Missing
`final_original_language` has 4589 (9.2%) missing values	Missing
`final_rating` has 4578 (9.2%) missing values	Missing
`final_production_countries` has 4578 (9.2%) missing values	Missing
`imdb_id` has 4579 (9.2%) missing values	Missing
`production_companies` has 4578 (9.2%) missing values	Missing
`cast` has 4578 (9.2%) missing values	Missing
`crew` has 4578 (9.2%) missing values	Missing
`director` has 23137 (46.4%) missing values	Missing
`director_id` has 23137 (46.4%) missing values	Missing
`star` has 23147 (46.4%) missing values	Missing
`star_id` has 23144 (46.4%) missing values	Missing
`final_domestic_boxoffice` has 804 (1.6%) zeros	Zeros
`final_rating` has 2936 (5.9%) zeros	Zeros

Reproduction

Analysis started	2025-03-26 21:47:56.704687
Analysis finished	2025-03-26 21:49:24.336762
Duration	1 minute and 27.63 seconds
Software version	ydata-profiling vv4.15.1
Download configuration	config.json

final_title
Text

Distinct	44940
Distinct (%)	90.1%
Missing	0
Missing (%)	0.0%
Memory size	389.7 KiB

Length

Max length	109
Median length	84
Mean length	16.260819
Min length	1

Characters and Unicode

Total characters	810862
Distinct characters	2946
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	40838 ?
Unique (%)	81.9%

Sample

1st row	!Women Art Revolution
2nd row	#1 Cheerleader Camp
3rd row	#chicagoGirl
4th row	#Horror
5th row	#Pellichoopulu

Value	Count	Frequency (%)
the	11602	8.0%
of	3698	2.6%
a	1844	1.3%
in	1386	1.0%
and	1205	0.8%
la	1041	0.7%
	918	0.6%
to	892	0.6%
de	739	0.5%
man	568	0.4%
Other values (35887)	120274	83.4%

Most occurring characters

Value	Count	Frequency (%)
	94281	11.6%
e	77683	9.6%
a	53486	6.6%
o	46165	5.7%
i	43055	5.3%
n	42932	5.3%
r	41452	5.1%
t	36838	4.5%
s	31340	3.9%
l	27841	3.4%
Other values (2936)	315789	38.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	810862	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	94281	11.6%
e	77683	9.6%
a	53486	6.6%
o	46165	5.7%
i	43055	5.3%
n	42932	5.3%
r	41452	5.1%
t	36838	4.5%
s	31340	3.9%
l	27841	3.4%
Other values (2936)	315789	38.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	810862	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	94281	11.6%
e	77683	9.6%
a	53486	6.6%
o	46165	5.7%
i	43055	5.3%
n	42932	5.3%
r	41452	5.1%
t	36838	4.5%
s	31340	3.9%
l	27841	3.4%
Other values (2936)	315789	38.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	810862	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	94281	11.6%
e	77683	9.6%
a	53486	6.6%
o	46165	5.7%
i	43055	5.3%
n	42932	5.3%
r	41452	5.1%
t	36838	4.5%
s	31340	3.9%
l	27841	3.4%
Other values (2936)	315789	38.9%

final_budget
Real number (ℝ)

High correlation Missing

Distinct	1348
Distinct (%)	9.7%
Missing	36038
Missing (%)	72.3%
Infinite	0
Infinite (%)	0.0%
Mean	25340963

Minimum	1
Maximum	5.332 × 10⁸
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	389.7 KiB

Quantile statistics

Minimum	1
5-th percentile	100000
Q1	2500000
median	10000000
Q3	30000000
95-th percentile	1.05 × 10⁸
Maximum	5.332 × 10⁸
Range	5.332 × 10⁸
Interquartile range (IQR)	27500000

Descriptive statistics

Standard deviation	39700100
Coefficient of variation (CV)	1.5666374
Kurtosis	13.674426
Mean	25340963
Median Absolute Deviation (MAD)	9050000
Skewness	3.1351164
Sum	3.5041483 × 10¹¹
Variance	1.576098 × 10¹⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000000	454	0.9%
5000000	432	0.9%
20000000	418	0.8%
15000000	360	0.7%
2000000	353	0.7%
30000000	333	0.7%
25000000	329	0.7%
3000000	326	0.7%
1000000	305	0.6%
40000000	297	0.6%
Other values (1338)	10221	20.5%
(Missing)	36038	72.3%

Value	Count	Frequency (%)
1	25	0.1%
2	14	< 0.1%
3	9	< 0.1%
4	7	< 0.1%
5	8	< 0.1%
6	5	< 0.1%
7	3	< 0.1%
8	5	< 0.1%
9	1	< 0.1%
10	10	< 0.1%

Value	Count	Frequency (%)
533200000	1	< 0.1%
400000000	3	< 0.1%
380000000	1	< 0.1%
379000000	1	< 0.1%
365000000	1	< 0.1%
340000000	1	< 0.1%
330400000	1	< 0.1%
300000000	5	< 0.1%
290000000	1	< 0.1%
280200000	1	< 0.1%

final_worldwide_boxoffice
Real number (ℝ)

High correlation Missing

Distinct	11446
Distinct (%)	90.2%
Missing	37177
Missing (%)	74.6%
Infinite	0
Infinite (%)	0.0%
Mean	78039564

Minimum	0
Maximum	2.923706 × 10⁹
Zeros	428
Zeros (%)	0.9%
Negative	0
Negative (%)	0.0%
Memory size	389.7 KiB

Quantile statistics

Minimum	0
5-th percentile	3005.8
Q1	2300000
median	18875011
Q3	74870866
95-th percentile	3.5837453 × 10⁸
Maximum	2.923706 × 10⁹
Range	2.923706 × 10⁹
Interquartile range (IQR)	72570866

Descriptive statistics

Standard deviation	1.6774213 × 10⁸
Coefficient of variation (CV)	2.1494499
Kurtosis	43.836131
Mean	78039564
Median Absolute Deviation (MAD)	18659672
Skewness	5.2419344
Sum	9.9024403 × 10¹¹
Variance	2.8137424 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	428	0.9%
11000000	23	< 0.1%
2000000	22	< 0.1%
10000000	22	< 0.1%
8000000	20	< 0.1%
6000000	20	< 0.1%
12000000	18	< 0.1%
5000000	17	< 0.1%
7000000	14	< 0.1%
3000000	13	< 0.1%
Other values (11436)	12092	24.2%
(Missing)	37177	74.6%

Value	Count	Frequency (%)
0	428	0.9%
1	12	< 0.1%
2	3	< 0.1%
3	9	< 0.1%
4	4	< 0.1%
5	4	< 0.1%
6	2	< 0.1%
7	3	< 0.1%
8	3	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
2923706026	1	< 0.1%
2748242781	1	< 0.1%
2743577587	1	< 0.1%
2320250281	1	< 0.1%
2223048786	1	< 0.1%
2068223624	1	< 0.1%
2056046835	1	< 0.1%
2048359754	1	< 0.1%
1979091486	1	< 0.1%
1921206586	1	< 0.1%

final_domestic_boxoffice
Real number (ℝ)

High correlation Missing Zeros

Distinct	12400
Distinct (%)	82.4%
Missing	34819
Missing (%)	69.8%
Infinite	0
Infinite (%)	0.0%
Mean	30254133

Minimum	0
Maximum	9.3666222 × 10⁸
Zeros	804
Zeros (%)	1.6%
Negative	0
Negative (%)	0.0%
Memory size	389.7 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	338837.5
median	6650206
Q3	33631822
95-th percentile	1.3670877 × 10⁸
Maximum	9.3666222 × 10⁸
Range	9.3666222 × 10⁸
Interquartile range (IQR)	33292984

Descriptive statistics

Standard deviation	61021707
Coefficient of variation (CV)	2.0169709
Kurtosis	34.621107
Mean	30254133
Median Absolute Deviation (MAD)	6637422
Skewness	4.7073205
Sum	4.5523394 × 10¹¹
Variance	3.7236487 × 10¹⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	804	1.6%
10000000	18	< 0.1%
7000000	15	< 0.1%
8000000	15	< 0.1%
4360000	14	< 0.1%
1000000	14	< 0.1%
5000000	14	< 0.1%
4000000	12	< 0.1%
2000000	11	< 0.1%
11000000	11	< 0.1%
Other values (12390)	14119	28.3%
(Missing)	34819	69.8%

Value	Count	Frequency (%)
0	804	1.6%
30	1	< 0.1%
80	1	< 0.1%
145	1	< 0.1%
181	1	< 0.1%
199	1	< 0.1%
252	2	< 0.1%
256	1	< 0.1%
264	1	< 0.1%
309	1	< 0.1%

Value	Count	Frequency (%)
936662225	2	< 0.1%
858373000	1	< 0.1%
814811535	1	< 0.1%
785221649	1	< 0.1%
749766139	1	< 0.1%
718732821	1	< 0.1%
700059566	1	< 0.1%
684075767	1	< 0.1%
678815482	1	< 0.1%
674460013	1	< 0.1%

final_genres
Text

Missing

Distinct	4071
Distinct (%)	8.8%
Missing	3706
Missing (%)	7.4%
Memory size	389.7 KiB

Length

Max length	264
Median length	225
Mean length	61.831282
Min length	2

Characters and Unicode

Total characters	2854132
Distinct characters	52
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2366 ?
Unique (%)	5.1%

Sample

1st row	[{'id': 99, 'name': 'Documentary'}]
2nd row	[{'id': 35, 'name': 'Comedy'}, {'id': 18, 'name': 'Drama'}]
3rd row	[{'id': 99, 'name': 'Documentary'}]
4th row	[{'id': 18, 'name': 'Drama'}, {'id': 9648, 'name': 'Mystery'}, {'id': 27, 'name': 'Horror'}, {'id': 53, 'name': 'Thriller'}]
5th row	[{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}]

Value	Count	Frequency (%)
id	90826	24.5%
name	90826	24.5%
drama	20432	5.5%
18	20208	5.5%
comedy	13329	3.6%
35	13163	3.6%
53	7601	2.1%
thriller	7601	2.1%
action	6721	1.8%
10749	6720	1.8%
Other values (40)	92962	25.1%

Most occurring characters

Value	Count	Frequency (%)
'	544956	19.1%
	324229	11.4%
:	181652	6.4%
a	153009	5.4%
e	147285	5.2%
m	144254	5.1%
,	138743	4.9%
i	130660	4.6%
n	126845	4.4%
d	107800	3.8%
Other values (42)	854699	29.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2854132	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	544956	19.1%
	324229	11.4%
:	181652	6.4%
a	153009	5.4%
e	147285	5.2%
m	144254	5.1%
,	138743	4.9%
i	130660	4.6%
n	126845	4.4%
d	107800	3.8%
Other values (42)	854699	29.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2854132	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	544956	19.1%
	324229	11.4%
:	181652	6.4%
a	153009	5.4%
e	147285	5.2%
m	144254	5.1%
,	138743	4.9%
i	130660	4.6%
n	126845	4.4%
d	107800	3.8%
Other values (42)	854699	29.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2854132	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	544956	19.1%
	324229	11.4%
:	181652	6.4%
a	153009	5.4%
e	147285	5.2%
m	144254	5.1%
,	138743	4.9%
i	130660	4.6%
n	126845	4.4%
d	107800	3.8%
Other values (42)	854699	29.9%

final_runtime
Real number (ℝ)

Missing

Distinct	353
Distinct (%)	0.8%
Missing	5534
Missing (%)	11.1%
Infinite	0
Infinite (%)	0.0%
Mean	97.730556

Minimum	0
Maximum	1256
Zeros	4
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	389.7 KiB

Quantile statistics

Minimum	0
5-th percentile	58
Q1	87
median	95
Q3	108
95-th percentile	139
Maximum	1256
Range	1256
Interquartile range (IQR)	21

Descriptive statistics

Standard deviation	34.455249
Coefficient of variation (CV)	0.35255349
Kurtosis	143.55352
Mean	97.730556
Median Absolute Deviation (MAD)	10
Skewness	6.7045416
Sum	4332591
Variance	1187.1642
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
90	2564	5.1%
100	1494	3.0%
95	1420	2.8%
93	1225	2.5%
96	1121	2.2%
92	1089	2.2%
91	1077	2.2%
94	1068	2.1%
97	1043	2.1%
98	1037	2.1%
Other values (343)	31194	62.6%
(Missing)	5534	11.1%

Value	Count	Frequency (%)
0	4	< 0.1%
1	107	0.2%
2	33	0.1%
3	48	0.1%
4	50	0.1%
5	51	0.1%
6	72	0.1%
7	103	0.2%
8	78	0.2%
9	63	0.1%

Value	Count	Frequency (%)
1256	1	< 0.1%
1140	2	< 0.1%
931	1	< 0.1%
925	1	< 0.1%
900	1	< 0.1%
877	1	< 0.1%
874	1	< 0.1%
840	2	< 0.1%
780	1	< 0.1%
720	1	< 0.1%

final_overview
Text

Missing

Distinct	44479
Distinct (%)	99.6%
Missing	5196
Missing (%)	10.4%
Memory size	389.7 KiB

Length

Max length	1000
Median length	787
Mean length	322.12505
Min length	1

Characters and Unicode

Total characters	14389326
Distinct characters	429
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	44447 ?
Unique (%)	99.5%

Sample

1st row	Through intimate interviews, provocative art, and rare, historical film and video footage, this feature documentary reveals how art addressing political consequences of discrimination and violence, the Feminist Art Revolution radically transformed the art and culture of our times.
2nd row	A pair of horny college guys get summer jobs at a sexy cheerleader camp.
3rd row	From her childhood bedroom in the Chicago suburbs, an American teenage girl uses social media to run the revolution in Syria. Armed with Facebook, Twitter, Skype and cameraphones, she helps her social network in Damascus and Homs braves snipers and shelling in the streets and the world the human rights atrocities of one of the most brutal dictators. But as the revolution rages on, everyone in the network must decide what is the most effective way to fight a dictator: social media or AK-47s.
4th row	Inspired by actual events, a group of 12 year old girls face a night of horror when the compulsive addiction of an online social media game turns a moment of cyber bullying into a night of insanity.
5th row	Raj Kandukuri and BiG Ben Films in association with Vinoothna Geetha presents #Pellichoopulu, a Telugu romantic comedy about two individuals Prashanth and Chitra who meet at a 'Pellichoopulu'. The story is about a modern day couple anchored down by their traditional roots. When fate plays havoc in their lives, they set off on a journey to find their dreams, face their fears and ultimately find true love. Directed by Tharun Bhascker of Anukokunda and Sainma fame, the film stars Vijay Deverakonda and Ritu Varma.

Value	Count	Frequency (%)
the	138243	5.6%
a	99167	4.0%
and	75338	3.1%
to	73417	3.0%
of	69678	2.8%
in	48286	2.0%
is	36579	1.5%
his	36235	1.5%
with	23925	1.0%
her	21490	0.9%
Other values (97290)	1830422	74.6%

Most occurring characters

Value	Count	Frequency (%)
	2411696	16.8%
e	1365824	9.5%
a	941961	6.5%
t	935949	6.5%
i	852797	5.9%
o	830980	5.8%
n	823680	5.7%
s	768967	5.3%
r	745341	5.2%
h	601526	4.2%
Other values (419)	4110605	28.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	14389326	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	2411696	16.8%
e	1365824	9.5%
a	941961	6.5%
t	935949	6.5%
i	852797	5.9%
o	830980	5.8%
n	823680	5.7%
s	768967	5.3%
r	745341	5.2%
h	601526	4.2%
Other values (419)	4110605	28.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	14389326	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	2411696	16.8%
e	1365824	9.5%
a	941961	6.5%
t	935949	6.5%
i	852797	5.9%
o	830980	5.8%
n	823680	5.7%
s	768967	5.3%
r	745341	5.2%
h	601526	4.2%
Other values (419)	4110605	28.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	14389326	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	2411696	16.8%
e	1365824	9.5%
a	941961	6.5%
t	935949	6.5%
i	852797	5.9%
o	830980	5.8%
n	823680	5.7%
s	768967	5.3%
r	745341	5.2%
h	601526	4.2%
Other values (419)	4110605	28.6%

final_certificate
Categorical

Missing

Distinct	30
Distinct (%)	0.1%
Missing	27216
Missing (%)	54.6%
Memory size	389.7 KiB

R	7592
Not Rated	4603
PG-13	2922
PG	2388
Approved	1720
Other values (25)	3425

Length

Max length	9
Median length	8
Mean length	4.357351
Min length	1

Characters and Unicode

Total characters	98694
Distinct characters	34
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Not Rated
2nd row	R
3rd row	R
4th row	R
5th row	R

Common Values

Value	Count	Frequency (%)
R	7592	15.2%
Not Rated	4603	9.2%
PG-13	2922	5.9%
PG	2388	4.8%
Approved	1720	3.4%
Passed	1256	2.5%
Unrated	693	1.4%
G	594	1.2%
TV-MA	228	0.5%
TV-14	208	0.4%
Other values (20)	446	0.9%
(Missing)	27216	54.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
r	7592	27.9%
not	4603	16.9%
rated	4603	16.9%
pg-13	2922	10.7%
pg	2388	8.8%
approved	1720	6.3%
passed	1256	4.6%
unrated	693	2.5%
g	594	2.2%
tv-ma	228	0.8%
Other values (20)	654	2.4%

Most occurring characters

Value	Count	Frequency (%)
R	12195	12.4%
t	9899	10.0%
e	8275	8.4%
d	8272	8.4%
P	6767	6.9%
a	6552	6.6%
o	6323	6.4%
G	6140	6.2%
N	4629	4.7%
	4603	4.7%
Other values (24)	25039	25.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	98694	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
R	12195	12.4%
t	9899	10.0%
e	8275	8.4%
d	8272	8.4%
P	6767	6.9%
a	6552	6.6%
o	6323	6.4%
G	6140	6.2%
N	4629	4.7%
	4603	4.7%
Other values (24)	25039	25.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	98694	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
R	12195	12.4%
t	9899	10.0%
e	8275	8.4%
d	8272	8.4%
P	6767	6.9%
a	6552	6.6%
o	6323	6.4%
G	6140	6.2%
N	4629	4.7%
	4603	4.7%
Other values (24)	25039	25.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	98694	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
R	12195	12.4%
t	9899	10.0%
e	8275	8.4%
d	8272	8.4%
P	6767	6.9%
a	6552	6.6%
o	6323	6.4%
G	6140	6.2%
N	4629	4.7%
	4603	4.7%
Other values (24)	25039	25.4%

final_original_language
Text

Missing

Distinct	89
Distinct (%)	0.2%
Missing	4589
Missing (%)	9.2%
Memory size	389.7 KiB

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	90554
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	17 ?
Unique (%)	< 0.1%

Sample

1st row	en
2nd row	en
3rd row	en
4th row	de
5th row	te

Value	Count	Frequency (%)
en	32138	71.0%
fr	2432	5.4%
it	1528	3.4%
ja	1345	3.0%
de	1076	2.4%
es	990	2.2%
ru	822	1.8%
hi	507	1.1%
ko	444	1.0%
zh	408	0.9%
Other values (79)	3587	7.9%

Most occurring characters

Value	Count	Frequency (%)
e	34458	38.1%
n	32846	36.3%
r	3625	4.0%
f	2827	3.1%
i	2385	2.6%
t	2249	2.5%
a	1833	2.0%
s	1648	1.8%
j	1346	1.5%
d	1320	1.5%
Other values (16)	6017	6.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	90554	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	34458	38.1%
n	32846	36.3%
r	3625	4.0%
f	2827	3.1%
i	2385	2.6%
t	2249	2.5%
a	1833	2.0%
s	1648	1.8%
j	1346	1.5%
d	1320	1.5%
Other values (16)	6017	6.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	90554	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	34458	38.1%
n	32846	36.3%
r	3625	4.0%
f	2827	3.1%
i	2385	2.6%
t	2249	2.5%
a	1833	2.0%
s	1648	1.8%
j	1346	1.5%
d	1320	1.5%
Other values (16)	6017	6.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	90554	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	34458	38.1%
n	32846	36.3%
r	3625	4.0%
f	2827	3.1%
i	2385	2.6%
t	2249	2.5%
a	1833	2.0%
s	1648	1.8%
j	1346	1.5%
d	1320	1.5%
Other values (16)	6017	6.6%

final_rating
Real number (ℝ)

Missing Zeros

Distinct	92
Distinct (%)	0.2%
Missing	4578
Missing (%)	9.2%
Infinite	0
Infinite (%)	0.0%
Mean	5.6249558

Minimum	0
Maximum	10
Zeros	2936
Zeros (%)	5.9%
Negative	0
Negative (%)	0.0%
Memory size	389.7 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	5
median	6
Q3	6.8
95-th percentile	7.8
Maximum	10
Range	10
Interquartile range (IQR)	1.8

Descriptive statistics

Standard deviation	1.9146519
Coefficient of variation (CV)	0.34038524
Kurtosis	2.5454047
Mean	5.6249558
Median Absolute Deviation (MAD)	0.9
Skewness	-1.5248665
Sum	254743
Variance	3.6658921
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2936	5.9%
6	2458	4.9%
5	1993	4.0%
7	1881	3.8%
6.5	1720	3.4%
6.3	1600	3.2%
5.5	1379	2.8%
5.8	1367	2.7%
6.4	1346	2.7%
6.7	1336	2.7%
Other values (82)	27272	54.7%
(Missing)	4578	9.2%

Value	Count	Frequency (%)
0	2936	5.9%
0.5	13	< 0.1%
0.7	1	< 0.1%
1	103	0.2%
1.1	1	< 0.1%
1.2	4	< 0.1%
1.3	13	< 0.1%
1.4	5	< 0.1%
1.5	30	0.1%
1.6	6	< 0.1%

Value	Count	Frequency (%)
10	184	0.4%
9.8	1	< 0.1%
9.6	1	< 0.1%
9.5	18	< 0.1%
9.4	3	< 0.1%
9.3	18	< 0.1%
9.2	4	< 0.1%
9.1	2	< 0.1%
9	158	0.3%
8.9	7	< 0.1%

final_clean_title
Text

Distinct	44730
Distinct (%)	89.7%
Missing	0
Missing (%)	0.0%
Memory size	389.7 KiB

Length

Max length	97
Median length	72
Mean length	14.370413
Min length	1

Characters and Unicode

Total characters	716595
Distinct characters	2831
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	40448 ?
Unique (%)	81.1%

Sample

1st row	!womenartrevolution
2nd row	#1cheerleadercamp
3rd row	#chicagogirl
4th row	#horror
5th row	#pellichoopulu

Value	Count	Frequency (%)
aliceinwonderland	10	< 0.1%
lesmisérables	9	< 0.1%
cinderella	9	< 0.1%
home	8	< 0.1%
thethreemusketeers	8	< 0.1%
wutheringheights	7	< 0.1%
macbeth	7	< 0.1%
peterpan	7	< 0.1%
hamlet	7	< 0.1%
achristmascarol	7	< 0.1%
Other values (44696)	49830	99.8%

Most occurring characters

Value	Count	Frequency (%)
e	80607	11.2%
a	59909	8.4%
t	50512	7.0%
o	48463	6.8%
i	47061	6.6%
n	45748	6.4%
r	45419	6.3%
s	41072	5.7%
l	34546	4.8%
h	30369	4.2%
Other values (2821)	232889	32.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	716595	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	80607	11.2%
a	59909	8.4%
t	50512	7.0%
o	48463	6.8%
i	47061	6.6%
n	45748	6.4%
r	45419	6.3%
s	41072	5.7%
l	34546	4.8%
h	30369	4.2%
Other values (2821)	232889	32.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	716595	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	80607	11.2%
a	59909	8.4%
t	50512	7.0%
o	48463	6.8%
i	47061	6.6%
n	45748	6.4%
r	45419	6.3%
s	41072	5.7%
l	34546	4.8%
h	30369	4.2%
Other values (2821)	232889	32.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	716595	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	80607	11.2%
a	59909	8.4%
t	50512	7.0%
o	48463	6.8%
i	47061	6.6%
n	45748	6.4%
r	45419	6.3%
s	41072	5.7%
l	34546	4.8%
h	30369	4.2%
Other values (2821)	232889	32.5%

final_production_countries
Text

Missing

Distinct	2388
Distinct (%)	5.3%
Missing	4578
Missing (%)	9.2%
Memory size	389.7 KiB

Length

Max length	1039
Median length	649
Mean length	53.268879
Min length	2

Characters and Unicode

Total characters	2412441
Distinct characters	65
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1768 ?
Unique (%)	3.9%

Sample

1st row	[]
2nd row	[{'iso_3166_1': 'US', 'name': 'United States of America'}]
3rd row	[]
4th row	[{'iso_3166_1': 'US', 'name': 'United States of America'}]
5th row	[{'iso_3166_1': 'IN', 'name': 'India'}]

Value	Count	Frequency (%)
iso_3166_1	49295	18.1%
name	49295	18.1%
united	25219	9.3%
states	21110	7.7%
of	21109	7.7%
america	21109	7.7%
us	21109	7.7%
	6199	2.3%
gb	4082	1.5%
kingdom	4082	1.5%
Other values (341)	49991	18.3%

Most occurring characters

Value	Count	Frequency (%)
'	394355	16.3%
	227312	9.4%
e	129783	5.4%
a	119624	5.0%
i	107731	4.5%
_	98590	4.1%
1	98590	4.1%
6	98590	4.1%
:	98590	4.1%
n	96683	4.0%
Other values (55)	942593	39.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2412441	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	394355	16.3%
	227312	9.4%
e	129783	5.4%
a	119624	5.0%
i	107731	4.5%
_	98590	4.1%
1	98590	4.1%
6	98590	4.1%
:	98590	4.1%
n	96683	4.0%
Other values (55)	942593	39.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2412441	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	394355	16.3%
	227312	9.4%
e	129783	5.4%
a	119624	5.0%
i	107731	4.5%
_	98590	4.1%
1	98590	4.1%
6	98590	4.1%
:	98590	4.1%
n	96683	4.0%
Other values (55)	942593	39.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2412441	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	394355	16.3%
	227312	9.4%
e	129783	5.4%
a	119624	5.0%
i	107731	4.5%
_	98590	4.1%
1	98590	4.1%
6	98590	4.1%
:	98590	4.1%
n	96683	4.0%
Other values (55)	942593	39.1%

imdb_id
Text

Missing

Distinct	45287
Distinct (%)	100.0%
Missing	4579
Missing (%)	9.2%
Memory size	389.7 KiB

Length

Max length	9
Median length	9
Mean length	9
Min length	9

Characters and Unicode

Total characters	407583
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	45287 ?
Unique (%)	100.0%

Sample

1st row	tt1699720
2nd row	tt1637976
3rd row	tt3060338
4th row	tt3526286
5th row	tt5824826

Value	Count	Frequency (%)
tt1699720	1	< 0.1%
tt0094592	1	< 0.1%
tt0065360	1	< 0.1%
tt2258233	1	< 0.1%
tt3060338	1	< 0.1%
tt3526286	1	< 0.1%
tt5824826	1	< 0.1%
tt5335198	1	< 0.1%
tt2106284	1	< 0.1%
tt1024733	1	< 0.1%
Other values (45277)	45277	> 99.9%

Most occurring characters

Value	Count	Frequency (%)
t	90574	22.2%
0	69728	17.1%
1	37099	9.1%
2	31112	7.6%
4	28394	7.0%
3	28012	6.9%
6	25362	6.2%
8	25325	6.2%
5	24174	5.9%
7	24130	5.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	407583	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
t	90574	22.2%
0	69728	17.1%
1	37099	9.1%
2	31112	7.6%
4	28394	7.0%
3	28012	6.9%
6	25362	6.2%
8	25325	6.2%
5	24174	5.9%
7	24130	5.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	407583	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
t	90574	22.2%
0	69728	17.1%
1	37099	9.1%
2	31112	7.6%
4	28394	7.0%
3	28012	6.9%
6	25362	6.2%
8	25325	6.2%
5	24174	5.9%
7	24130	5.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	407583	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
t	90574	22.2%
0	69728	17.1%
1	37099	9.1%
2	31112	7.6%
4	28394	7.0%
3	28012	6.9%
6	25362	6.2%
8	25325	6.2%
5	24174	5.9%
7	24130	5.9%

production_companies
Text

Missing

Distinct	22670
Distinct (%)	50.1%
Missing	4578
Missing (%)	9.2%
Memory size	389.7 KiB

Length

Max length	1252
Median length	954
Mean length	70.181638
Min length	2

Characters and Unicode

Total characters	3178386
Distinct characters	293
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	20327 ?
Unique (%)	44.9%

Sample

1st row	[]
2nd row	[]
3rd row	[]
4th row	[{'name': 'AST Studios', 'id': 75277}, {'name': 'Lowland Pictures', 'id': 75278}]
5th row	[{'name': 'BigBen Films', 'id': 75835}, {'name': 'Vinoothna Geetha', 'id': 75836}]

Value	Count	Frequency (%)
name	70357	17.6%
id	70357	17.6%
	12613	3.2%
films	9432	2.4%
pictures	9247	2.3%
productions	9043	2.3%
film	6665	1.7%
entertainment	5139	1.3%
corporation	2187	0.5%
company	1762	0.4%
Other values (42149)	203289	50.8%

Most occurring characters

Value	Count	Frequency (%)
'	421734	13.3%
	354816	11.2%
i	177054	5.6%
e	164782	5.2%
n	160119	5.0%
a	147306	4.6%
:	140721	4.4%
m	114521	3.6%
,	107598	3.4%
d	103751	3.3%
Other values (283)	1285984	40.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3178386	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	421734	13.3%
	354816	11.2%
i	177054	5.6%
e	164782	5.2%
n	160119	5.0%
a	147306	4.6%
:	140721	4.4%
m	114521	3.6%
,	107598	3.4%
d	103751	3.3%
Other values (283)	1285984	40.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3178386	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	421734	13.3%
	354816	11.2%
i	177054	5.6%
e	164782	5.2%
n	160119	5.0%
a	147306	4.6%
:	140721	4.4%
m	114521	3.6%
,	107598	3.4%
d	103751	3.3%
Other values (283)	1285984	40.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3178386	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	421734	13.3%
	354816	11.2%
i	177054	5.6%
e	164782	5.2%
n	160119	5.0%
a	147306	4.6%
:	140721	4.4%
m	114521	3.6%
,	107598	3.4%
d	103751	3.3%
Other values (283)	1285984	40.5%

release_date
Date

Distinct	18155
Distinct (%)	36.5%
Missing	149
Missing (%)	0.3%
Memory size	389.7 KiB

Minimum	1874-12-09 00:00:00
Maximum	2068-12-11 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

final_year
Real number (ℝ)

Distinct	182
Distinct (%)	0.4%
Missing	149
Missing (%)	0.3%
Infinite	0
Infinite (%)	0.0%
Mean	1993.5121

Minimum	1874
Maximum	2068
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	389.7 KiB

Quantile statistics

Minimum	1874
5-th percentile	1942
Q1	1981
median	2003
Q3	2011
95-th percentile	2016
Maximum	2068
Range	194
Interquartile range (IQR)	30

Descriptive statistics

Standard deviation	23.87865
Coefficient of variation (CV)	0.011978182
Kurtosis	1.1391916
Mean	1993.5121
Median Absolute Deviation (MAD)	11
Skewness	-1.2328701
Sum	99111440
Variance	570.18992
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2014	2163	4.3%
2015	2147	4.3%
2013	2047	4.1%
2012	1894	3.8%
2011	1848	3.7%
2016	1765	3.5%
2009	1745	3.5%
2010	1698	3.4%
2008	1647	3.3%
2007	1476	3.0%
Other values (172)	31287	62.7%

Value	Count	Frequency (%)
1874	1	< 0.1%
1878	1	< 0.1%
1883	1	< 0.1%
1887	1	< 0.1%
1888	2	< 0.1%
1890	5	< 0.1%
1891	6	< 0.1%
1892	3	< 0.1%
1893	1	< 0.1%
1894	13	< 0.1%

Value	Count	Frequency (%)
2068	8	< 0.1%
2067	9	< 0.1%
2066	6	< 0.1%
2065	7	< 0.1%
2064	8	< 0.1%
2063	8	< 0.1%
2062	8	< 0.1%
2061	5	< 0.1%
2060	5	< 0.1%
2059	4	< 0.1%

cast
Text

Missing

Distinct	42946
Distinct (%)	94.8%
Missing	4578
Missing (%)	9.2%
Memory size	389.7 KiB

Length

Max length	60040
Median length	8169
Mean length	2398.365
Min length	2

Characters and Unicode

Total characters	108617152
Distinct characters	729
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	42945 ?
Unique (%)	94.8%

Sample

1st row	[{'cast_id': 1001, 'character': 'Herself', 'credit_id': '52fe48c3c3a36847f8178269', 'gender': 1, 'id': 213613, 'name': 'Lynn Hershman Leeson', 'order': 0, 'profile_path': '/jE1eBrttgiI6Hd21SkMRPaZ9K9v.jpg'}]
2nd row	[{'cast_id': 1, 'character': 'Charlene Tilton', 'credit_id': '52fe45c4c3a36847f80d96e5', 'gender': 1, 'id': 21862, 'name': 'Charlene Tilton', 'order': 0, 'profile_path': '/jZwoQorUzQXTbwENKDCYPIbCGxl.jpg'}, {'cast_id': 2, 'character': 'Michael', 'credit_id': '52fe45c4c3a36847f80d96e9', 'gender': 2, 'id': 67154, 'name': 'Jay Gillespie', 'order': 1, 'profile_path': '/v5gOyjHBfUjh6yLEljUDAxrUFWu.jpg'}, {'cast_id': 3, 'character': 'Britt', 'credit_id': '52fe45c4c3a36847f80d96ed', 'gender': 1, 'id': 77756, 'name': 'Harmony Blossom', 'order': 2, 'profile_path': '/aTHBIbzxCVwAfBxXmnbDa5js1wU.jpg'}, {'cast_id': 9, 'character': 'Zan', 'credit_id': '5585a7e6c3a3682746000a53', 'gender': 2, 'id': 971237, 'name': 'Hector David Jr.', 'order': 3, 'profile_path': '/soCsXUn7OD4fDSDarFFlOxsyvFr.jpg'}]
3rd row	[]
4th row	[{'cast_id': 0, 'character': "Alex's 12-Step Friend", 'credit_id': '545bba84c3a3685358001b80', 'gender': 1, 'id': 343, 'name': 'Taryn Manning', 'order': 1, 'profile_path': '/ujPqJgRvOVaTgVI5qTWHBSM6BB3.jpg'}, {'cast_id': 1, 'character': "Sam's Mom", 'credit_id': '545bba8a0e0a261fad0023f6', 'gender': 1, 'id': 10871, 'name': 'Natasha Lyonne', 'order': 2, 'profile_path': '/8rhl25eCPQQFhv1Mvqe9eMP3MpS.jpg'}, {'cast_id': 2, 'character': 'Alex Cox', 'credit_id': '545bba8fc3a36853500018a4', 'gender': 1, 'id': 2838, 'name': 'Chloë Sevigny', 'order': 3, 'profile_path': '/qhVabrmmSwfhbApuagf0NlEhBaf.jpg'}, {'cast_id': 3, 'character': 'Mr. Cox', 'credit_id': '545bba94c3a3685353001a56', 'gender': 2, 'id': 9296, 'name': 'Balthazar Getty', 'order': 4, 'profile_path': '/F7k9JnUfbqIUvd124B0HQVT05h.jpg'}, {'cast_id': 4, 'character': 'Dr. White', 'credit_id': '545bba990e0a261fb900220b', 'gender': 2, 'id': 16327, 'name': 'Timothy Hutton', 'order': 5, 'profile_path': '/ypC4mzLExwmG0QHfi8vFe9LTeSi.jpg'}, {'cast_id': 5, 'character': 'Lisa', 'credit_id': '545bba9ec3a368535d001e67', 'gender': 1, 'id': 210573, 'name': 'Lydia Hearst', 'order': 6, 'profile_path': '/qtG7roaFf06dSX0BrgCNNcKtpfY.jpg'}, {'cast_id': 6, 'character': 'Mom', 'credit_id': '545bbaa4c3a368535d001e6b', 'gender': 0, 'id': 180425, 'name': 'Jessica Blank', 'order': 7, 'profile_path': '/4YXsdyncSuXGqeKysTVut2gjCCR.jpg'}, {'cast_id': 7, 'character': 'Molly', 'credit_id': '545bbab1c3a3685362001a0f', 'gender': 0, 'id': 1102331, 'name': 'Annabelle Dexter-Jones', 'order': 8, 'profile_path': '/iwze7ysPnKAjCXCtYXrep4MwVaF.jpg'}, {'cast_id': 15, 'character': 'Tatiana (voice)', 'credit_id': '572f9a8792514102ac000642', 'gender': 1, 'id': 61111, 'name': 'Tara Subkoff', 'order': 9, 'profile_path': '/qBbSymmytAOqgAGlll3sN5LXih3.jpg'}]
5th row	[{'cast_id': 0, 'character': 'Prashanth', 'credit_id': '5718614ac3a3687c2c00337c', 'gender': 2, 'id': 1508809, 'name': 'Vijay Deverakonda', 'order': 0, 'profile_path': '/7H4NUc9y5Cld0QZHigRVNWTYeA2.jpg'}, {'cast_id': 1, 'character': 'Chitra', 'credit_id': '5718615e925141282f003046', 'gender': 0, 'id': 1608576, 'name': 'Ritu Varma', 'order': 1, 'profile_path': '/hdQsWD26r5iOldntgOfDfmNct3z.jpg'}, {'cast_id': 11, 'character': '', 'credit_id': '5897a0adc3a3686d9e0001e1', 'gender': 0, 'id': 1441726, 'name': 'Nandoo', 'order': 2, 'profile_path': '/mhoSOfjGPB7pWSVpiAXLOUwNrmD.jpg'}, {'cast_id': 14, 'character': '', 'credit_id': '5897a1f7c3a36877150000c8', 'gender': 0, 'id': 1751708, 'name': 'Priyadarshi Pullikonda', 'order': 3, 'profile_path': '/32yf9gYAJjjRoeCJDY88qOGnJk.jpg'}, {'cast_id': 13, 'character': '', 'credit_id': '5897a18e9251417a7f000082', 'gender': 0, 'id': 1751705, 'name': 'Abhay Bethiganti', 'order': 4, 'profile_path': '/em7eqBETITCP0ZI8cEO5ae0dupt.jpg'}, {'cast_id': 9, 'character': '', 'credit_id': '589783a89251415aaa01727a', 'gender': 0, 'id': 1060294, 'name': 'Anish Kuruvilla', 'order': 5, 'profile_path': '/qtf9rH4b86YsF4ltLLd37Iz3QPK.jpg'}, {'cast_id': 12, 'character': '', 'credit_id': '5897a115c3a3687715000048', 'gender': 0, 'id': 101861, 'name': 'Gururaj Manepalli', 'order': 6, 'profile_path': '/ufJmM1tFTxpFlFuDCHA6QtpcRlF.jpg'}, {'cast_id': 15, 'character': '', 'credit_id': '5897a554c3a368771d000298', 'gender': 0, 'id': 1751737, 'name': 'Kedar Shankara', 'order': 7, 'profile_path': '/tq8jcMjVdAwsKJN8Gqc9ujD7ezR.jpg'}]

Value	Count	Frequency (%)
character	561369	5.6%
name	561356	5.6%
order	561355	5.6%
id	561350	5.6%
gender	561345	5.6%
profile_path	561344	5.6%
credit_id	561344	5.6%
cast_id	561344	5.6%
2	292509	2.9%
0	262987	2.6%
Other values (1051839)	5047442	50.0%

Most occurring characters

Value	Count	Frequency (%)
'	13104869	12.1%
	10048630	9.3%
e	6289905	5.8%
r	5064494	4.7%
a	4859522	4.5%
:	4491198	4.1%
,	4454432	4.1%
d	4228537	3.9%
i	3883533	3.6%
c	3460903	3.2%
Other values (719)	48731129	44.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	108617152	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	13104869	12.1%
	10048630	9.3%
e	6289905	5.8%
r	5064494	4.7%
a	4859522	4.5%
:	4491198	4.1%
,	4454432	4.1%
d	4228537	3.9%
i	3883533	3.6%
c	3460903	3.2%
Other values (719)	48731129	44.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	108617152	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	13104869	12.1%
	10048630	9.3%
e	6289905	5.8%
r	5064494	4.7%
a	4859522	4.5%
:	4491198	4.1%
,	4454432	4.1%
d	4228537	3.9%
i	3883533	3.6%
c	3460903	3.2%
Other values (719)	48731129	44.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	108617152	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	13104869	12.1%
	10048630	9.3%
e	6289905	5.8%
r	5064494	4.7%
a	4859522	4.5%
:	4491198	4.1%
,	4454432	4.1%
d	4228537	3.9%
i	3883533	3.6%
c	3460903	3.2%
Other values (719)	48731129	44.9%

crew
Text

Missing

Distinct	44568
Distinct (%)	98.4%
Missing	4578
Missing (%)	9.2%
Memory size	389.7 KiB

Length

Max length	73601
Median length	14058
Mean length	1769.8422
Min length	2

Characters and Unicode

Total characters	80152613
Distinct characters	364
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	44567 ?
Unique (%)	98.4%

Sample

1st row	[{'credit_id': '52fe48c3c3a36847f8178265', 'department': 'Directing', 'gender': 1, 'id': 213613, 'job': 'Director', 'name': 'Lynn Hershman Leeson', 'profile_path': '/jE1eBrttgiI6Hd21SkMRPaZ9K9v.jpg'}, {'credit_id': '557ef4ed9251410a2c002056', 'department': 'Production', 'gender': 0, 'id': 1475661, 'job': 'Producer', 'name': 'Ariel Dougherty', 'profile_path': '/hhEnbQQ7jFlqMPf6p5lTwnAbop1.jpg'}]
2nd row	[{'credit_id': '52fe45c4c3a36847f80d96f3', 'department': 'Directing', 'gender': 2, 'id': 128762, 'job': 'Director', 'name': 'Mark Quod', 'profile_path': None}, {'credit_id': '52fe45c4c3a36847f80d96f9', 'department': 'Production', 'gender': 2, 'id': 30053, 'job': 'Producer', 'name': 'David Michael Latt', 'profile_path': None}, {'credit_id': '52fe45c4c3a36847f80d9705', 'department': 'Sound', 'gender': 2, 'id': 128763, 'job': 'Original Music Composer', 'name': 'Chris Ridenhour', 'profile_path': None}, {'credit_id': '538b2e14c3a3687155000f8a', 'department': 'Production', 'gender': 2, 'id': 236844, 'job': 'Executive Producer', 'name': 'David Rimawi', 'profile_path': None}, {'credit_id': '56a7d89fc3a36828af001e64', 'department': 'Writing', 'gender': 1, 'id': 146005, 'job': 'Writer', 'name': 'Naomi L. Selfman', 'profile_path': None}]
3rd row	[{'credit_id': '5362c9a7c3a368156f00049f', 'department': 'Directing', 'gender': 2, 'id': 50584, 'job': 'Director', 'name': 'Joe Piscatella', 'profile_path': None}, {'credit_id': '5362c9ebc3a368158d0004c1', 'department': 'Editing', 'gender': 2, 'id': 50584, 'job': 'Editor', 'name': 'Joe Piscatella', 'profile_path': None}, {'credit_id': '5362c9cec3a368157600044f', 'department': 'Production', 'gender': 2, 'id': 50584, 'job': 'Producer', 'name': 'Joe Piscatella', 'profile_path': None}, {'credit_id': '5362c9bbc3a368156f0004a1', 'department': 'Writing', 'gender': 2, 'id': 50584, 'job': 'Writer', 'name': 'Joe Piscatella', 'profile_path': None}, {'credit_id': '5362c9fbc3a368157d000448', 'department': 'Production', 'gender': 2, 'id': 1099063, 'job': 'Producer', 'name': 'Mark Rinehart', 'profile_path': None}, {'credit_id': '5362ca0fc3a36815950004c7', 'department': 'Editing', 'gender': 0, 'id': 1099064, 'job': 'Editor', 'name': 'Jeff Castelluccio', 'profile_path': None}]
4th row	[{'credit_id': '545bbabf0e0a261fb9002212', 'department': 'Directing', 'gender': 1, 'id': 61111, 'job': 'Director', 'name': 'Tara Subkoff', 'profile_path': '/qBbSymmytAOqgAGlll3sN5LXih3.jpg'}, {'credit_id': '545bbac70e0a261fb6002329', 'department': 'Writing', 'gender': 1, 'id': 61111, 'job': 'Screenplay', 'name': 'Tara Subkoff', 'profile_path': '/qBbSymmytAOqgAGlll3sN5LXih3.jpg'}, {'credit_id': '545bbad3c3a3685358001b92', 'department': 'Production', 'gender': 0, 'id': 1382445, 'job': 'Producer', 'name': 'Jason Ludman', 'profile_path': None}, {'credit_id': '545bbadbc3a368535d001e74', 'department': 'Production', 'gender': 0, 'id': 1382446, 'job': 'Producer', 'name': 'Oren Segal', 'profile_path': None}, {'credit_id': '545bbae4c3a36853500018a8', 'department': 'Production', 'gender': 1, 'id': 61111, 'job': 'Producer', 'name': 'Tara Subkoff', 'profile_path': '/qBbSymmytAOqgAGlll3sN5LXih3.jpg'}, {'credit_id': '545bbaf3c3a3685358001b9d', 'department': 'Production', 'gender': 0, 'id': 1382448, 'job': 'Producer', 'name': 'Brendan Walsh', 'profile_path': None}]
5th row	[{'credit_id': '571862bbc3a3687fd60029dd', 'department': 'Camera', 'gender': 0, 'id': 1608578, 'job': 'Director of Photography', 'name': 'Nagesh Bannel', 'profile_path': None}, {'credit_id': '571862f5c3a3687bc7002af5', 'department': 'Sound', 'gender': 0, 'id': 1608580, 'job': 'Music Director', 'name': 'Vivek Saagar', 'profile_path': None}, {'credit_id': '58979fae925141730000017e', 'department': 'Directing', 'gender': 0, 'id': 1673599, 'job': 'Director', 'name': 'Tharun Bhascker Dhaassyam', 'profile_path': None}, {'credit_id': '584ad597c3a368141a021fb3', 'department': 'Writing', 'gender': 0, 'id': 1673599, 'job': 'Writer', 'name': 'Tharun Bhascker Dhaassyam', 'profile_path': None}, {'credit_id': '584acff7c3a368142801db85', 'department': 'Production', 'gender': 0, 'id': 1673602, 'job': 'Producer', 'name': 'Yash Rangineni', 'profile_path': None}, {'credit_id': '584acfe092514119bf01fee6', 'department': 'Production', 'gender': 0, 'id': 1720222, 'job': 'Producer', 'name': 'Raj Kandukuri', 'profile_path': None}]

Value	Count	Frequency (%)
department	467071	6.3%
job	463124	6.3%
name	463094	6.3%
gender	463094	6.3%
profile_path	463094	6.3%
id	463094	6.3%
credit_id	463094	6.3%
none	368196	5.0%
0	271544	3.7%
2	160523	2.2%
Other values (728059)	3333506	45.2%

Most occurring characters

Value	Count	Frequency (%)
'	10375307	12.9%
	7334210	9.2%
e	5437896	6.8%
r	3379503	4.2%
:	3241660	4.0%
i	3215013	4.0%
,	3197238	4.0%
d	3156032	3.9%
t	2922853	3.6%
a	2899567	3.6%
Other values (354)	34993334	43.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	80152613	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	10375307	12.9%
	7334210	9.2%
e	5437896	6.8%
r	3379503	4.2%
:	3241660	4.0%
i	3215013	4.0%
,	3197238	4.0%
d	3156032	3.9%
t	2922853	3.6%
a	2899567	3.6%
Other values (354)	34993334	43.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	80152613	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	10375307	12.9%
	7334210	9.2%
e	5437896	6.8%
r	3379503	4.2%
:	3241660	4.0%
i	3215013	4.0%
,	3197238	4.0%
d	3156032	3.9%
t	2922853	3.6%
a	2899567	3.6%
Other values (354)	34993334	43.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	80152613	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	10375307	12.9%
	7334210	9.2%
e	5437896	6.8%
r	3379503	4.2%
:	3241660	4.0%
i	3215013	4.0%
,	3197238	4.0%
d	3156032	3.9%
t	2922853	3.6%
a	2899567	3.6%
Other values (354)	34993334	43.7%

director
Text

Missing

Distinct	12011
Distinct (%)	44.9%
Missing	23137
Missing (%)	46.4%
Memory size	389.7 KiB

Length

Max length	923
Median length	477
Mean length	15.167159
Min length	3

Characters and Unicode

Total characters	405403
Distinct characters	98
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	7825 ?
Unique (%)	29.3%

Sample

1st row	Tara Subkoff
2nd row	Tharun Bhascker Dhaassyam
3rd row	Lyubomyr Levytsky
4th row	Seth Grossman
5th row	Tatia Rosenthal

Value	Count	Frequency (%)
john	851	1.4%
robert	568	0.9%
michael	556	0.9%
david	523	0.8%
william	395	0.6%
richard	366	0.6%
peter	327	0.5%
george	307	0.5%
james	306	0.5%
paul	273	0.4%
Other values (13024)	57592	92.8%

Most occurring characters

Value	Count	Frequency (%)
	35335	8.7%
a	34394	8.5%
e	33912	8.4%
r	26624	6.6%
n	26623	6.6%
i	25711	6.3%
o	23667	5.8%
l	18108	4.5%
s	13653	3.4%
t	13045	3.2%
Other values (88)	154331	38.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	405403	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	35335	8.7%
a	34394	8.5%
e	33912	8.4%
r	26624	6.6%
n	26623	6.6%
i	25711	6.3%
o	23667	5.8%
l	18108	4.5%
s	13653	3.4%
t	13045	3.2%
Other values (88)	154331	38.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	405403	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	35335	8.7%
a	34394	8.5%
e	33912	8.4%
r	26624	6.6%
n	26623	6.6%
i	25711	6.3%
o	23667	5.8%
l	18108	4.5%
s	13653	3.4%
t	13045	3.2%
Other values (88)	154331	38.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	405403	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	35335	8.7%
a	34394	8.5%
e	33912	8.4%
r	26624	6.6%
n	26623	6.6%
i	25711	6.3%
o	23667	5.8%
l	18108	4.5%
s	13653	3.4%
t	13045	3.2%
Other values (88)	154331	38.1%

director_id
Text

Missing

Distinct	11216
Distinct (%)	42.0%
Missing	23137
Missing (%)	46.4%
Memory size	389.7 KiB

Length

Max length	17
Median length	16
Mean length	16.000374
Min length	16

Characters and Unicode

Total characters	427674
Distinct characters	15
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	6867 ?
Unique (%)	25.7%

Sample

1st row	/name/nm0836964/
2nd row	/name/nm5056902/
3rd row	/name/nm2463500/
4th row	/name/nm0343713/
5th row	/name/nm1038127/

Value	Count	Frequency (%)
name/nm0002031	49	0.2%
name/nm0000033	48	0.2%
name/nm0000406	45	0.2%
name/nm0861703	36	0.1%
name/nm0000485	34	0.1%
name/nm0368871	34	0.1%
name/nm0586281	34	0.1%
name/nm0936404	33	0.1%
name/nm0909825	33	0.1%
name/nm0496746	33	0.1%
Other values (11206)	26350	98.6%

Most occurring characters

Value	Count	Frequency (%)
/	80187	18.7%
n	53458	12.5%
m	53458	12.5%
0	47312	11.1%
a	26729	6.2%
e	26729	6.2%
1	18790	4.4%
2	16788	3.9%
3	15641	3.7%
4	15590	3.6%
Other values (5)	72992	17.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	427674	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
/	80187	18.7%
n	53458	12.5%
m	53458	12.5%
0	47312	11.1%
a	26729	6.2%
e	26729	6.2%
1	18790	4.4%
2	16788	3.9%
3	15641	3.7%
4	15590	3.6%
Other values (5)	72992	17.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	427674	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
/	80187	18.7%
n	53458	12.5%
m	53458	12.5%
0	47312	11.1%
a	26729	6.2%
e	26729	6.2%
1	18790	4.4%
2	16788	3.9%
3	15641	3.7%
4	15590	3.6%
Other values (5)	72992	17.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	427674	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
/	80187	18.7%
n	53458	12.5%
m	53458	12.5%
0	47312	11.1%
a	26729	6.2%
e	26729	6.2%
1	18790	4.4%
2	16788	3.9%
3	15641	3.7%
4	15590	3.6%
Other values (5)	72992	17.1%

star
Text

Missing

Distinct	26611
Distinct (%)	99.6%
Missing	23147
Missing (%)	46.4%
Memory size	389.7 KiB

Length

Max length	105
Median length	93
Mean length	61.814439
Min length	10

Characters and Unicode

Total characters	1651620
Distinct characters	107
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	26526 ?
Unique (%)	99.3%

Sample

1st row	Sadie Seelert, Haley Murphy, Bridget McGarry, Blue Lindeberg
2nd row	Abhay Bethiganti, Keshav Deepak, Vijay Deverakonda, Anish Kuruvilla
3rd row	Sergei Zorenko, Boris Savenko, Kseniya Mishina, Arthur Shurypa
4th row	Ross Patterson, Jessie Wiseman, Seth Grossman, Lauren Aboulafia
5th row	Geoffrey Rush, Anthony LaPaglia, Samuel Johnson, Barry Otto

Value	Count	Frequency (%)
john	1708	0.8%
michael	1351	0.6%
robert	1192	0.5%
james	1129	0.5%
david	971	0.4%
richard	910	0.4%
lee	737	0.3%
peter	719	0.3%
paul	667	0.3%
william	604	0.3%
Other values (35645)	209369	95.4%

Most occurring characters

Value	Count	Frequency (%)
	192638	11.7%
a	136334	8.3%
e	124873	7.6%
n	100683	6.1%
r	92549	5.6%
i	91440	5.5%
	79995	4.8%
,	79995	4.8%
o	79265	4.8%
l	66874	4.0%
Other values (97)	606974	36.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1651620	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	192638	11.7%
a	136334	8.3%
e	124873	7.6%
n	100683	6.1%
r	92549	5.6%
i	91440	5.5%
	79995	4.8%
,	79995	4.8%
o	79265	4.8%
l	66874	4.0%
Other values (97)	606974	36.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1651620	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	192638	11.7%
a	136334	8.3%
e	124873	7.6%
n	100683	6.1%
r	92549	5.6%
i	91440	5.5%
	79995	4.8%
,	79995	4.8%
o	79265	4.8%
l	66874	4.0%
Other values (97)	606974	36.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1651620	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	192638	11.7%
a	136334	8.3%
e	124873	7.6%
n	100683	6.1%
r	92549	5.6%
i	91440	5.5%
	79995	4.8%
,	79995	4.8%
o	79265	4.8%
l	66874	4.0%
Other values (97)	606974	36.8%

star_id
Text

Missing

Distinct	26627
Distinct (%)	99.6%
Missing	23144
Missing (%)	46.4%
Memory size	389.7 KiB

Length

Max length	1053
Median length	67
Mean length	68.680301
Min length	16

Characters and Unicode

Total characters	1835275
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	26551 ?
Unique (%)	99.4%

Sample

1st row	/name/nm6344380/,/name/nm4239131/,/name/nm5376482/,/name/nm6344381/
2nd row	/name/nm8232982/,/name/nm6642302/,/name/nm4797922/,/name/nm2378839/
3rd row	/name/nm7881765/,/name/nm7881762/,/name/nm2432008/,/name/nm7881761/
4th row	/name/nm0666388/,/name/nm3034435/,/name/nm0343713/,/name/nm2992430/
5th row	/name/nm0001691/,/name/nm0001439/,/name/nm0426170/,/name/nm0653222/

Value	Count	Frequency (%)
name/nm0000638/,/name/nm0000559/,/name/nm0001420/,/name/nm0001150	6	< 0.1%
name/nm5752523/,/name/nm0424453/,/name/nm3940484/,/name/nm1870939	4	< 0.1%
name/nm0000230/,/name/nm0001735/,/name/nm0949350/,/name/nm0001835	4	< 0.1%
name/nm0793840/,/name/nm0436778/,/name/nm0757327/,/name/nm0757087/,/name/nm0394679	3	< 0.1%
name/nm0793840/,/name/nm2976492/,/name/nm1543455/,/name/nm1543296/,/name/nm0594646	3	< 0.1%
name/nm0802325/,/name/nm0482121/,/name/nm0799982/,/name/nm1230870	3	< 0.1%
name/nm0395950/,/name/nm1543455/,/name/nm0436778/,/name/nm0837358	3	< 0.1%
name/nm0000858/,/name/nm0397397/,/name/nm0132682/,/name/nm0219666	3	< 0.1%
name/nm0905152/,/name/nm0000206/,/name/nm0000401/,/name/nm0005251/,/name/nm0915989	3	< 0.1%
name/nm0819825/,/name/nm0344655/,/name/nm0120381/,/name/nm0910432	3	< 0.1%
Other values (26617)	26687	99.9%

Most occurring characters

Value	Count	Frequency (%)
/	328557	17.9%
n	219038	11.9%
m	219038	11.9%
0	217441	11.8%
a	109519	6.0%
e	109519	6.0%
,	82797	4.5%
1	78689	4.3%
2	65137	3.5%
4	61765	3.4%
Other values (6)	343775	18.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1835275	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
/	328557	17.9%
n	219038	11.9%
m	219038	11.9%
0	217441	11.8%
a	109519	6.0%
e	109519	6.0%
,	82797	4.5%
1	78689	4.3%
2	65137	3.5%
4	61765	3.4%
Other values (6)	343775	18.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1835275	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
/	328557	17.9%
n	219038	11.9%
m	219038	11.9%
0	217441	11.8%
a	109519	6.0%
e	109519	6.0%
,	82797	4.5%
1	78689	4.3%
2	65137	3.5%
4	61765	3.4%
Other values (6)	343775	18.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1835275	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
/	328557	17.9%
n	219038	11.9%
m	219038	11.9%
0	217441	11.8%
a	109519	6.0%
e	109519	6.0%
,	82797	4.5%
1	78689	4.3%
2	65137	3.5%
4	61765	3.4%
Other values (6)	343775	18.7%

_merge
Categorical

Imbalance

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	49.0 KiB

left_only	43266
right_only	4578
both	2022

Length

Max length	10
Median length	9
Mean length	8.8890627
Min length	4

Characters and Unicode

Total characters	443262
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	left_only
2nd row	left_only
3rd row	left_only
4th row	both
5th row	left_only

Common Values

Value	Count	Frequency (%)
left_only	43266	86.8%
right_only	4578	9.2%
both	2022	4.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
left_only	43266	86.8%
right_only	4578	9.2%
both	2022	4.1%

Most occurring characters

Value	Count	Frequency (%)
l	91110	20.6%
t	49866	11.2%
o	49866	11.2%
_	47844	10.8%
n	47844	10.8%
y	47844	10.8%
e	43266	9.8%
f	43266	9.8%
h	6600	1.5%
r	4578	1.0%
Other values (3)	11178	2.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	443262	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
l	91110	20.6%
t	49866	11.2%
o	49866	11.2%
_	47844	10.8%
n	47844	10.8%
y	47844	10.8%
e	43266	9.8%
f	43266	9.8%
h	6600	1.5%
r	4578	1.0%
Other values (3)	11178	2.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	443262	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
l	91110	20.6%
t	49866	11.2%
o	49866	11.2%
_	47844	10.8%
n	47844	10.8%
y	47844	10.8%
e	43266	9.8%
f	43266	9.8%
h	6600	1.5%
r	4578	1.0%
Other values (3)	11178	2.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	443262	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
l	91110	20.6%
t	49866	11.2%
o	49866	11.2%
_	47844	10.8%
n	47844	10.8%
y	47844	10.8%
e	43266	9.8%
f	43266	9.8%
h	6600	1.5%
r	4578	1.0%
Other values (3)	11178	2.5%

Interactions

Correlations

	_merge	final_budget	final_certificate	final_domestic_boxoffice	final_rating	final_runtime	final_worldwide_boxoffice	final_year
_merge	1.000	0.113	0.227	0.097	0.084	0.046	0.057	0.206
final_budget	0.113	1.000	0.126	0.665	0.047	0.367	0.725	0.130
final_certificate	0.227	0.126	1.000	0.067	0.069	0.085	0.065	0.403
final_domestic_boxoffice	0.097	0.665	0.067	1.000	0.091	0.199	0.915	-0.036
final_rating	0.084	0.047	0.069	0.091	1.000	0.181	0.120	-0.008
final_runtime	0.046	0.367	0.085	0.199	0.181	1.000	0.255	0.065
final_worldwide_boxoffice	0.057	0.725	0.065	0.915	0.120	0.255	1.000	0.024
final_year	0.206	0.130	0.403	-0.036	-0.008	0.065	0.024	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

	final_title	final_budget	final_worldwide_boxoffice	final_domestic_boxoffice	final_genres	final_runtime	final_overview	final_certificate	final_original_language	final_rating	final_clean_title	final_production_countries	imdb_id	production_companies	release_date	final_year	cast	crew	director	director_id	star	star_id	_merge
0	!Women Art Revolution	NaN	NaN	NaN	[{'id': 99, 'name': 'Documentary'}]	83.0	Through intimate interviews, provocative art, and rare, historical film and video footage, this feature documentary reveals how art addressing political consequences of discrimination and violence, the Feminist Art Revolution radically transformed the art and culture of our times.	NaN	en	4.3	!womenartrevolution	[]	tt1699720	[]	2010-01-01	2010.0	[{'cast_id': 1001, 'character': 'Herself', 'credit_id': '52fe48c3c3a36847f8178269', 'gender': 1, 'id': 213613, 'name': 'Lynn Hershman Leeson', 'order': 0, 'profile_path': '/jE1eBrttgiI6Hd21SkMRPaZ9K9v.jpg'}]	[{'credit_id': '52fe48c3c3a36847f8178265', 'department': 'Directing', 'gender': 1, 'id': 213613, 'job': 'Director', 'name': 'Lynn Hershman Leeson', 'profile_path': '/jE1eBrttgiI6Hd21SkMRPaZ9K9v.jpg'}, {'credit_id': '557ef4ed9251410a2c002056', 'department': 'Production', 'gender': 0, 'id': 1475661, 'job': 'Producer', 'name': 'Ariel Dougherty', 'profile_path': '/hhEnbQQ7jFlqMPf6p5lTwnAbop1.jpg'}]	NaN	NaN	NaN	NaN	left_only
1	#1 Cheerleader Camp	NaN	NaN	NaN	[{'id': 35, 'name': 'Comedy'}, {'id': 18, 'name': 'Drama'}]	95.0	A pair of horny college guys get summer jobs at a sexy cheerleader camp.	NaN	en	3.4	#1cheerleadercamp	[{'iso_3166_1': 'US', 'name': 'United States of America'}]	tt1637976	[]	2010-07-27	2010.0	[{'cast_id': 1, 'character': 'Charlene Tilton', 'credit_id': '52fe45c4c3a36847f80d96e5', 'gender': 1, 'id': 21862, 'name': 'Charlene Tilton', 'order': 0, 'profile_path': '/jZwoQorUzQXTbwENKDCYPIbCGxl.jpg'}, {'cast_id': 2, 'character': 'Michael', 'credit_id': '52fe45c4c3a36847f80d96e9', 'gender': 2, 'id': 67154, 'name': 'Jay Gillespie', 'order': 1, 'profile_path': '/v5gOyjHBfUjh6yLEljUDAxrUFWu.jpg'}, {'cast_id': 3, 'character': 'Britt', 'credit_id': '52fe45c4c3a36847f80d96ed', 'gender': 1, 'id': 77756, 'name': 'Harmony Blossom', 'order': 2, 'profile_path': '/aTHBIbzxCVwAfBxXmnbDa5js1wU.jpg'}, {'cast_id': 9, 'character': 'Zan', 'credit_id': '5585a7e6c3a3682746000a53', 'gender': 2, 'id': 971237, 'name': 'Hector David Jr.', 'order': 3, 'profile_path': '/soCsXUn7OD4fDSDarFFlOxsyvFr.jpg'}]	[{'credit_id': '52fe45c4c3a36847f80d96f3', 'department': 'Directing', 'gender': 2, 'id': 128762, 'job': 'Director', 'name': 'Mark Quod', 'profile_path': None}, {'credit_id': '52fe45c4c3a36847f80d96f9', 'department': 'Production', 'gender': 2, 'id': 30053, 'job': 'Producer', 'name': 'David Michael Latt', 'profile_path': None}, {'credit_id': '52fe45c4c3a36847f80d9705', 'department': 'Sound', 'gender': 2, 'id': 128763, 'job': 'Original Music Composer', 'name': 'Chris Ridenhour', 'profile_path': None}, {'credit_id': '538b2e14c3a3687155000f8a', 'department': 'Production', 'gender': 2, 'id': 236844, 'job': 'Executive Producer', 'name': 'David Rimawi', 'profile_path': None}, {'credit_id': '56a7d89fc3a36828af001e64', 'department': 'Writing', 'gender': 1, 'id': 146005, 'job': 'Writer', 'name': 'Naomi L. Selfman', 'profile_path': None}]	NaN	NaN	NaN	NaN	left_only
2	#chicagoGirl	NaN	NaN	NaN	[{'id': 99, 'name': 'Documentary'}]	74.0	From her childhood bedroom in the Chicago suburbs, an American teenage girl uses social media to run the revolution in Syria. Armed with Facebook, Twitter, Skype and cameraphones, she helps her social network in Damascus and Homs braves snipers and shelling in the streets and the world the human rights atrocities of one of the most brutal dictators. But as the revolution rages on, everyone in the network must decide what is the most effective way to fight a dictator: social media or AK-47s.	NaN	en	7.0	#chicagogirl	[]	tt3060338	[]	2013-11-21	2013.0	[]	[{'credit_id': '5362c9a7c3a368156f00049f', 'department': 'Directing', 'gender': 2, 'id': 50584, 'job': 'Director', 'name': 'Joe Piscatella', 'profile_path': None}, {'credit_id': '5362c9ebc3a368158d0004c1', 'department': 'Editing', 'gender': 2, 'id': 50584, 'job': 'Editor', 'name': 'Joe Piscatella', 'profile_path': None}, {'credit_id': '5362c9cec3a368157600044f', 'department': 'Production', 'gender': 2, 'id': 50584, 'job': 'Producer', 'name': 'Joe Piscatella', 'profile_path': None}, {'credit_id': '5362c9bbc3a368156f0004a1', 'department': 'Writing', 'gender': 2, 'id': 50584, 'job': 'Writer', 'name': 'Joe Piscatella', 'profile_path': None}, {'credit_id': '5362c9fbc3a368157d000448', 'department': 'Production', 'gender': 2, 'id': 1099063, 'job': 'Producer', 'name': 'Mark Rinehart', 'profile_path': None}, {'credit_id': '5362ca0fc3a36815950004c7', 'department': 'Editing', 'gender': 0, 'id': 1099064, 'job': 'Editor', 'name': 'Jeff Castelluccio', 'profile_path': None}]	NaN	NaN	NaN	NaN	left_only
3	#Horror	1500000.0	0.0	0.0	[{'id': 18, 'name': 'Drama'}, {'id': 9648, 'name': 'Mystery'}, {'id': 27, 'name': 'Horror'}, {'id': 53, 'name': 'Thriller'}]	90.0	Inspired by actual events, a group of 12 year old girls face a night of horror when the compulsive addiction of an online social media game turns a moment of cyber bullying into a night of insanity.	Not Rated	de	3.4	#horror	[{'iso_3166_1': 'US', 'name': 'United States of America'}]	tt3526286	[{'name': 'AST Studios', 'id': 75277}, {'name': 'Lowland Pictures', 'id': 75278}]	2015-11-20	2015.0	[{'cast_id': 0, 'character': "Alex's 12-Step Friend", 'credit_id': '545bba84c3a3685358001b80', 'gender': 1, 'id': 343, 'name': 'Taryn Manning', 'order': 1, 'profile_path': '/ujPqJgRvOVaTgVI5qTWHBSM6BB3.jpg'}, {'cast_id': 1, 'character': "Sam's Mom", 'credit_id': '545bba8a0e0a261fad0023f6', 'gender': 1, 'id': 10871, 'name': 'Natasha Lyonne', 'order': 2, 'profile_path': '/8rhl25eCPQQFhv1Mvqe9eMP3MpS.jpg'}, {'cast_id': 2, 'character': 'Alex Cox', 'credit_id': '545bba8fc3a36853500018a4', 'gender': 1, 'id': 2838, 'name': 'Chloë Sevigny', 'order': 3, 'profile_path': '/qhVabrmmSwfhbApuagf0NlEhBaf.jpg'}, {'cast_id': 3, 'character': 'Mr. Cox', 'credit_id': '545bba94c3a3685353001a56', 'gender': 2, 'id': 9296, 'name': 'Balthazar Getty', 'order': 4, 'profile_path': '/F7k9JnUfbqIUvd124B0HQVT05h.jpg'}, {'cast_id': 4, 'character': 'Dr. White', 'credit_id': '545bba990e0a261fb900220b', 'gender': 2, 'id': 16327, 'name': 'Timothy Hutton', 'order': 5, 'profile_path': '/ypC4mzLExwmG0QHfi8vFe9LTeSi.jpg'}, {'cast_id': 5, 'character': 'Lisa', 'credit_id': '545bba9ec3a368535d001e67', 'gender': 1, 'id': 210573, 'name': 'Lydia Hearst', 'order': 6, 'profile_path': '/qtG7roaFf06dSX0BrgCNNcKtpfY.jpg'}, {'cast_id': 6, 'character': 'Mom', 'credit_id': '545bbaa4c3a368535d001e6b', 'gender': 0, 'id': 180425, 'name': 'Jessica Blank', 'order': 7, 'profile_path': '/4YXsdyncSuXGqeKysTVut2gjCCR.jpg'}, {'cast_id': 7, 'character': 'Molly', 'credit_id': '545bbab1c3a3685362001a0f', 'gender': 0, 'id': 1102331, 'name': 'Annabelle Dexter-Jones', 'order': 8, 'profile_path': '/iwze7ysPnKAjCXCtYXrep4MwVaF.jpg'}, {'cast_id': 15, 'character': 'Tatiana (voice)', 'credit_id': '572f9a8792514102ac000642', 'gender': 1, 'id': 61111, 'name': 'Tara Subkoff', 'order': 9, 'profile_path': '/qBbSymmytAOqgAGlll3sN5LXih3.jpg'}]	[{'credit_id': '545bbabf0e0a261fb9002212', 'department': 'Directing', 'gender': 1, 'id': 61111, 'job': 'Director', 'name': 'Tara Subkoff', 'profile_path': '/qBbSymmytAOqgAGlll3sN5LXih3.jpg'}, {'credit_id': '545bbac70e0a261fb6002329', 'department': 'Writing', 'gender': 1, 'id': 61111, 'job': 'Screenplay', 'name': 'Tara Subkoff', 'profile_path': '/qBbSymmytAOqgAGlll3sN5LXih3.jpg'}, {'credit_id': '545bbad3c3a3685358001b92', 'department': 'Production', 'gender': 0, 'id': 1382445, 'job': 'Producer', 'name': 'Jason Ludman', 'profile_path': None}, {'credit_id': '545bbadbc3a368535d001e74', 'department': 'Production', 'gender': 0, 'id': 1382446, 'job': 'Producer', 'name': 'Oren Segal', 'profile_path': None}, {'credit_id': '545bbae4c3a36853500018a8', 'department': 'Production', 'gender': 1, 'id': 61111, 'job': 'Producer', 'name': 'Tara Subkoff', 'profile_path': '/qBbSymmytAOqgAGlll3sN5LXih3.jpg'}, {'credit_id': '545bbaf3c3a3685358001b9d', 'department': 'Production', 'gender': 0, 'id': 1382448, 'job': 'Producer', 'name': 'Brendan Walsh', 'profile_path': None}]	Tara Subkoff	/name/nm0836964/	Sadie Seelert, \nHaley Murphy, \nBridget McGarry, \nBlue Lindeberg	/name/nm6344380/,/name/nm4239131/,/name/nm5376482/,/name/nm6344381/	both
4	#Pellichoopulu	200000.0	5500000.0	NaN	[{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}]	124.0	Raj Kandukuri and BiG Ben Films in association with Vinoothna Geetha presents #Pellichoopulu, a Telugu romantic comedy about two individuals Prashanth and Chitra who meet at a 'Pellichoopulu'. The story is about a modern day couple anchored down by their traditional roots. When fate plays havoc in their lives, they set off on a journey to find their dreams, face their fears and ultimately find true love. Directed by Tharun Bhascker of Anukokunda and Sainma fame, the film stars Vijay Deverakonda and Ritu Varma.	NaN	te	7.8	#pellichoopulu	[{'iso_3166_1': 'IN', 'name': 'India'}]	tt5824826	[{'name': 'BigBen Films', 'id': 75835}, {'name': 'Vinoothna Geetha', 'id': 75836}]	2016-07-29	2016.0	[{'cast_id': 0, 'character': 'Prashanth', 'credit_id': '5718614ac3a3687c2c00337c', 'gender': 2, 'id': 1508809, 'name': 'Vijay Deverakonda', 'order': 0, 'profile_path': '/7H4NUc9y5Cld0QZHigRVNWTYeA2.jpg'}, {'cast_id': 1, 'character': 'Chitra', 'credit_id': '5718615e925141282f003046', 'gender': 0, 'id': 1608576, 'name': 'Ritu Varma', 'order': 1, 'profile_path': '/hdQsWD26r5iOldntgOfDfmNct3z.jpg'}, {'cast_id': 11, 'character': '', 'credit_id': '5897a0adc3a3686d9e0001e1', 'gender': 0, 'id': 1441726, 'name': 'Nandoo', 'order': 2, 'profile_path': '/mhoSOfjGPB7pWSVpiAXLOUwNrmD.jpg'}, {'cast_id': 14, 'character': '', 'credit_id': '5897a1f7c3a36877150000c8', 'gender': 0, 'id': 1751708, 'name': 'Priyadarshi Pullikonda', 'order': 3, 'profile_path': '/32yf9gYAJjjRoeCJDY88qOGnJk.jpg'}, {'cast_id': 13, 'character': '', 'credit_id': '5897a18e9251417a7f000082', 'gender': 0, 'id': 1751705, 'name': 'Abhay Bethiganti', 'order': 4, 'profile_path': '/em7eqBETITCP0ZI8cEO5ae0dupt.jpg'}, {'cast_id': 9, 'character': '', 'credit_id': '589783a89251415aaa01727a', 'gender': 0, 'id': 1060294, 'name': 'Anish Kuruvilla', 'order': 5, 'profile_path': '/qtf9rH4b86YsF4ltLLd37Iz3QPK.jpg'}, {'cast_id': 12, 'character': '', 'credit_id': '5897a115c3a3687715000048', 'gender': 0, 'id': 101861, 'name': 'Gururaj Manepalli', 'order': 6, 'profile_path': '/ufJmM1tFTxpFlFuDCHA6QtpcRlF.jpg'}, {'cast_id': 15, 'character': '', 'credit_id': '5897a554c3a368771d000298', 'gender': 0, 'id': 1751737, 'name': 'Kedar Shankara', 'order': 7, 'profile_path': '/tq8jcMjVdAwsKJN8Gqc9ujD7ezR.jpg'}]	[{'credit_id': '571862bbc3a3687fd60029dd', 'department': 'Camera', 'gender': 0, 'id': 1608578, 'job': 'Director of Photography', 'name': 'Nagesh Bannel', 'profile_path': None}, {'credit_id': '571862f5c3a3687bc7002af5', 'department': 'Sound', 'gender': 0, 'id': 1608580, 'job': 'Music Director', 'name': 'Vivek Saagar', 'profile_path': None}, {'credit_id': '58979fae925141730000017e', 'department': 'Directing', 'gender': 0, 'id': 1673599, 'job': 'Director', 'name': 'Tharun Bhascker Dhaassyam', 'profile_path': None}, {'credit_id': '584ad597c3a368141a021fb3', 'department': 'Writing', 'gender': 0, 'id': 1673599, 'job': 'Writer', 'name': 'Tharun Bhascker Dhaassyam', 'profile_path': None}, {'credit_id': '584acff7c3a368142801db85', 'department': 'Production', 'gender': 0, 'id': 1673602, 'job': 'Producer', 'name': 'Yash Rangineni', 'profile_path': None}, {'credit_id': '584acfe092514119bf01fee6', 'department': 'Production', 'gender': 0, 'id': 1720222, 'job': 'Producer', 'name': 'Raj Kandukuri', 'profile_path': None}]	Tharun Bhascker Dhaassyam	/name/nm5056902/	Abhay Bethiganti, \nKeshav Deepak, \nVijay Deverakonda, \nAnish Kuruvilla	/name/nm8232982/,/name/nm6642302/,/name/nm4797922/,/name/nm2378839/	left_only
5	#SELFIEPARTY	NaN	NaN	NaN	[{'id': 35, 'name': 'Comedy'}]	90.0	Four friends who are all students, wake up at the police station, not remembering the events of yesterday. They are accused of murdering a dwarf, whose body was found on the lawn of the house where the boys partied last night. To figure out what happened, the boys decide to collect all the photos and videos from yesterday's mayhem.	NaN	uk	0.0	#selfieparty	[{'iso_3166_1': 'UA', 'name': 'Ukraine'}]	tt5335198	[]	2016-03-31	2016.0	[{'cast_id': 1, 'character': '', 'credit_id': '56ef3f31c3a368226000ce52', 'gender': 1, 'id': 1593567, 'name': 'Nadiya Lukavetska ', 'order': 1, 'profile_path': '/mMbFytMa1ByOmOgzE0xhjFufEM.jpg'}]	[{'credit_id': '56ef3c16c3a368225300ccb1', 'department': 'Directing', 'gender': 0, 'id': 1086533, 'job': 'Director', 'name': 'Lubomir Levitski', 'profile_path': None}]	Lyubomyr Levytsky	/name/nm2463500/	Sergei Zorenko, \nBoris Savenko, \nKseniya Mishina, \nArthur Shurypa	/name/nm7881765/,/name/nm7881762/,/name/nm2432008/,/name/nm7881761/	left_only
6	$50K and a Call Girl: A Love Story	NaN	NaN	NaN	[{'id': 18, 'name': 'Drama'}]	90.0	When Ross is diagnosed with terminal brain cancer and given six weeks to live, his newly engaged older brother Seth offers to spend his $50,000 wedding fund on a final trip of a lifetime. Their plans are complicated when Ross invites a call girl to join the group and Seth’s uptight fiancée insists on tagging along. This raucous road trip comedy features hip-hop star Asher Roth.	R	en	6.3	$50kandacallgirl:alovestory	[{'iso_3166_1': 'US', 'name': 'United States of America'}]	tt2106284	[]	2014-01-10	2014.0	[{'cast_id': 2, 'character': 'Ross', 'credit_id': '52fe4f31c3a36847f82c42ad', 'gender': 2, 'id': 77809, 'name': 'Ross Patterson', 'order': 0, 'profile_path': '/3Qd6FIEjAoakyFpgm4e0wxrzvzP.jpg'}, {'cast_id': 3, 'character': 'Carly', 'credit_id': '52fe4f31c3a36847f82c42b1', 'gender': 1, 'id': 228276, 'name': 'Jessie Wiseman', 'order': 1, 'profile_path': '/r5Qaj5Epj1KULIOOVqoHoPiHL7I.jpg'}, {'cast_id': 4, 'character': 'Seth', 'credit_id': '52fe4f31c3a36847f82c42b5', 'gender': 2, 'id': 87438, 'name': 'Seth Grossman', 'order': 2, 'profile_path': None}, {'cast_id': 5, 'character': 'Lauren', 'credit_id': '52fe4f31c3a36847f82c42b9', 'gender': 0, 'id': 1286162, 'name': 'Lauren Aboulafia', 'order': 3, 'profile_path': None}, {'cast_id': 8, 'character': 'Asher', 'credit_id': '58414508c3a36865b300531a', 'gender': 0, 'id': 1717286, 'name': 'Asher Roth', 'order': 4, 'profile_path': None}, {'cast_id': 9, 'character': 'Penelope', 'credit_id': '584145159251417d500055fe', 'gender': 1, 'id': 210346, 'name': 'Keena Ferguson', 'order': 5, 'profile_path': '/l3Sf2uUwpFvPCvJfiBj9H3PiUmE.jpg'}, {'cast_id': 10, 'character': 'Jesse Winchester', 'credit_id': '5841452c9251417d620055df', 'gender': 2, 'id': 1717282, 'name': 'Al Carabello', 'order': 6, 'profile_path': '/33NyJLAxt2KOVQDxpmHL6Ytxmat.jpg'}]	[{'credit_id': '52fe4f31c3a36847f82c42c5', 'department': 'Writing', 'gender': 2, 'id': 77809, 'job': 'Writer', 'name': 'Ross Patterson', 'profile_path': '/3Qd6FIEjAoakyFpgm4e0wxrzvzP.jpg'}, {'credit_id': '52fe4f31c3a36847f82c42a9', 'department': 'Directing', 'gender': 2, 'id': 87438, 'job': 'Director', 'name': 'Seth Grossman', 'profile_path': None}, {'credit_id': '52fe4f31c3a36847f82c42bf', 'department': 'Writing', 'gender': 2, 'id': 87438, 'job': 'Writer', 'name': 'Seth Grossman', 'profile_path': None}]	Seth Grossman	/name/nm0343713/	Ross Patterson, \nJessie Wiseman, \nSeth Grossman, \nLauren Aboulafia	/name/nm0666388/,/name/nm3034435/,/name/nm0343713/,/name/nm2992430/	left_only
7	$5 a Day	NaN	NaN	NaN	[{'id': 18, 'name': 'Drama'}, {'id': 35, 'name': 'Comedy'}]	98.0	After being released from jail, the son of a con man joins his father on the road.	NaN	en	6.0	$5aday	[{'iso_3166_1': 'US', 'name': 'United States of America'}]	tt1024733	[{'name': 'New Line Cinema', 'id': 12}]	2008-01-01	2008.0	[{'cast_id': 13, 'character': 'Nat Parker', 'credit_id': '52fe43b2c3a36847f8068855', 'gender': 2, 'id': 4690, 'name': 'Christopher Walken', 'order': 0, 'profile_path': '/ysO1GwRzLT9OVAB9Y2SKHxomqDr.jpg'}, {'cast_id': 14, 'character': 'Ritchie Flynn Parker', 'credit_id': '52fe43b2c3a36847f8068859', 'gender': 2, 'id': 4941, 'name': 'Alessandro Nivola', 'order': 1, 'profile_path': '/lLlaotVNM6dhjXj7GWVLSedugct.jpg'}, {'cast_id': 12, 'character': 'Dolores Jones', 'credit_id': '52fe43b2c3a36847f8068851', 'gender': 1, 'id': 4430, 'name': 'Sharon Stone', 'order': 2, 'profile_path': '/m57fGJemBTpsjydGlaZJywlIWz4.jpg'}, {'cast_id': 15, 'character': 'Rick Carlson', 'credit_id': '52fe43b2c3a36847f806885d', 'gender': 2, 'id': 21721, 'name': 'Dean Cain', 'order': 3, 'profile_path': '/cICjOmo5KZWdfJLBvIExDE6Ma5f.jpg'}, {'cast_id': 16, 'character': 'Maggie', 'credit_id': '52fe43b2c3a36847f8068861', 'gender': 1, 'id': 2956, 'name': 'Amanda Peet', 'order': 4, 'profile_path': '/81KzrntoeEztNpfhCYNgfOtI3kU.jpg'}, {'cast_id': 9, 'character': 'Tim Webber', 'credit_id': '52fe43b2c3a36847f8068845', 'gender': 2, 'id': 36135, 'name': 'Christopher Dempsey', 'order': 5, 'profile_path': '/nOX8sCxl0LRFYMkYauWFD0xwaDm.jpg'}, {'cast_id': 10, 'character': 'Mrs. Carlson', 'credit_id': '52fe43b2c3a36847f8068849', 'gender': 0, 'id': 36136, 'name': 'Bridget Ann White', 'order': 6, 'profile_path': '/ysgN1bjaiC7Pwts12eF3jD8EmfS.jpg'}, {'cast_id': 11, 'character': 'Sherry', 'credit_id': '52fe43b2c3a36847f806884d', 'gender': 1, 'id': 36137, 'name': 'Nectar Rose', 'order': 7, 'profile_path': '/p5DyM7147ELNpuBXIUbz0LteBuQ.jpg'}, {'cast_id': 17, 'character': '', 'credit_id': '52fe43b2c3a36847f8068865', 'gender': 2, 'id': 9979, 'name': 'Peter Coyote', 'order': 8, 'profile_path': '/5zVvYZxE6T0OeL1iaFBBCzY3QOi.jpg'}]	[{'credit_id': '52fe43b2c3a36847f8068835', 'department': 'Production', 'gender': 2, 'id': 1593, 'job': 'Casting', 'name': 'Joseph Middleton', 'profile_path': None}, {'credit_id': '52fe43b2c3a36847f8068817', 'department': 'Directing', 'gender': 2, 'id': 24248, 'job': 'Director', 'name': 'Nigel Cole', 'profile_path': '/2CIcwfX3zzzTYqUPUQzKdnUgQl7.jpg'}, {'credit_id': '52fe43b2c3a36847f806881d', 'department': 'Writing', 'gender': 0, 'id': 36129, 'job': 'Screenplay', 'name': 'Neal H. Dobrofsky', 'profile_path': None}, {'credit_id': '52fe43b2c3a36847f8068823', 'department': 'Writing', 'gender': 0, 'id': 36130, 'job': 'Screenplay', 'name': 'Tippi Dobrofsky', 'profile_path': None}, {'credit_id': '52fe43b2c3a36847f8068829', 'department': 'Production', 'gender': 1, 'id': 36131, 'job': 'Producer', 'name': 'Carol Baum', 'profile_path': None}, {'credit_id': '52fe43b2c3a36847f806882f', 'department': 'Production', 'gender': 1, 'id': 36132, 'job': 'Producer', 'name': 'Jane Goldenring', 'profile_path': None}, {'credit_id': '52fe43b2c3a36847f806883b', 'department': 'Art', 'gender': 0, 'id': 36133, 'job': 'Production Design', 'name': 'Bryce Perrin', 'profile_path': None}, {'credit_id': '52fe43b2c3a36847f8068841', 'department': 'Production', 'gender': 0, 'id': 36134, 'job': 'Producer', 'name': 'Kia Jam', 'profile_path': None}]	NaN	NaN	NaN	NaN	left_only
8	$9.99	NaN	NaN	52107.0	[{'id': 16, 'name': 'Animation'}, {'id': 18, 'name': 'Drama'}]	78.0	Have you ever wondered "What is the meaning of life? Why do we exist?" The answer to this vexing question is now within your reach! You'll find it in a small yet amazing booklet, which will explain, in easy to follow, simple terms your reason for being! The booklet, printed on the finest paper, contains illuminating, exquisite colour pictures, and could be yours for a mere $9.99.	R	en	6.0	$9.99	[{'iso_3166_1': 'AU', 'name': 'Australia'}, {'iso_3166_1': 'IL', 'name': 'Israel'}]	tt0790799	[{'name': 'Australian Film Finance Corporation', 'id': 1380}]	2008-09-04	2008.0	[{'cast_id': 4, 'character': 'Bisley (voice)', 'credit_id': '52fe47cf9251416c750a6281', 'gender': 2, 'id': 37289, 'name': 'Tom Budge', 'order': 0, 'profile_path': '/yu5L2Rw36Y6to5YMcjI3JXMfIBH.jpg'}, {'cast_id': 5, 'character': 'n/a', 'credit_id': '52fe47cf9251416c750a6285', 'gender': 0, 'id': 84450, 'name': 'Josef Ber', 'order': 1, 'profile_path': '/4pKNxJpfr6Ow5adomvHSIkBg4qt.jpg'}, {'cast_id': 6, 'character': 'Ron (voice)', 'credit_id': '52fe47cf9251416c750a6289', 'gender': 2, 'id': 33192, 'name': 'Joel Edgerton', 'order': 2, 'profile_path': '/lkOkaMKSRRGLMgkLaCzR9sYgTgx.jpg'}, {'cast_id': 7, 'character': 'Stanton (voice)', 'credit_id': '52fe47cf9251416c750a628d', 'gender': 2, 'id': 84451, 'name': 'Leon Ford', 'order': 3, 'profile_path': None}, {'cast_id': 8, 'character': 'Dave Peck (voice)', 'credit_id': '52fe47cf9251416c750a6291', 'gender': 2, 'id': 77138, 'name': 'Samuel Johnson', 'order': 4, 'profile_path': '/8X6DZna6wS9jx4Gext3QNtbtcPH.jpg'}, {'cast_id': 9, 'character': 'Michelle (voice)', 'credit_id': '52fe47cf9251416c750a6295', 'gender': 1, 'id': 79966, 'name': 'Claudia Karvan', 'order': 5, 'profile_path': '/4M0Z25W9hI2ihSa6xBrdFxmBdTD.jpg'}, {'cast_id': 10, 'character': 'Zack (voice)', 'credit_id': '52fe47cf9251416c750a6299', 'gender': 2, 'id': 84452, 'name': 'Jamie Katsamatsas', 'order': 6, 'profile_path': None}, {'cast_id': 11, 'character': 'Jim Peck (voice)', 'credit_id': '52fe47cf9251416c750a629d', 'gender': 2, 'id': 57829, 'name': 'Anthony LaPaglia', 'order': 7, 'profile_path': '/22sOEc37TsxxcnIl1XmucuW3IDl.jpg'}, {'cast_id': 12, 'character': 'Lenny Peck (voice)', 'credit_id': '52fe47cf9251416c750a62a1', 'gender': 2, 'id': 77335, 'name': 'Ben Mendelsohn', 'order': 8, 'profile_path': '/nAeZkSUXh9CUAUq1cFAg77rZLIS.jpg'}, {'cast_id': 13, 'character': 'Angel (voice)', 'credit_id': '52fe47cf9251416c750a62a5', 'gender': 2, 'id': 118, 'name': 'Geoffrey Rush', 'order': 9, 'profile_path': '/5h91WHSK80YtqTk1bMiar2IZzO2.jpg'}]	[{'credit_id': '52fe47cf9251416c750a627d', 'department': 'Writing', 'gender': 0, 'id': 55046, 'job': 'Screenplay', 'name': 'Etgar Keret', 'profile_path': None}, {'credit_id': '5734e7c09251417b3e00059f', 'department': 'Writing', 'gender': 1, 'id': 84448, 'job': 'Screenplay', 'name': 'Tatia Rosenthal', 'profile_path': None}, {'credit_id': '52fe47cf9251416c750a6271', 'department': 'Directing', 'gender': 1, 'id': 84448, 'job': 'Director', 'name': 'Tatia Rosenthal', 'profile_path': None}, {'credit_id': '552eb7f1c3a36804cd0019a9', 'department': 'Visual Effects', 'gender': 0, 'id': 1448052, 'job': 'Animation', 'name': 'Anthony Elworthy', 'profile_path': None}, {'credit_id': '552eb7b9c3a368750100465a', 'department': 'Visual Effects', 'gender': 0, 'id': 1453480, 'job': 'Animation', 'name': 'Daniel Alderson', 'profile_path': None}, {'credit_id': '552eb7fbc3a3687501004669', 'department': 'Visual Effects', 'gender': 0, 'id': 1453527, 'job': 'Animation', 'name': 'Jan-Erik Maas', 'profile_path': None}, {'credit_id': '552eb80ec3a368413100305e', 'department': 'Visual Effects', 'gender': 0, 'id': 1453649, 'job': 'Animation', 'name': 'Andy Spilsted', 'profile_path': None}, {'credit_id': '552eb7c4c3a3686be2003960', 'department': 'Visual Effects', 'gender': 0, 'id': 1454649, 'job': 'Animation', 'name': 'Yonatan Bereskin', 'profile_path': None}, {'credit_id': '552eb7d0c3a3686c4e0037a3', 'department': 'Visual Effects', 'gender': 0, 'id': 1454650, 'job': 'Animation', 'name': 'Darren Burgess', 'profile_path': None}, {'credit_id': '552eb7e7c3a36804cd0019a0', 'department': 'Visual Effects', 'gender': 0, 'id': 1454651, 'job': 'Animation', 'name': 'Steve Cox', 'profile_path': None}, {'credit_id': '552eb80592514103ce007dd9', 'department': 'Visual Effects', 'gender': 0, 'id': 1454652, 'job': 'Animation', 'name': 'Sharon Parker', 'profile_path': None}, {'credit_id': '552eb8199251413b3b000fd2', 'department': 'Visual Effects', 'gender': 0, 'id': 1454653, 'job': 'Animation', 'name': 'Norman Yeend', 'profile_path': None}]	Tatia Rosenthal	/name/nm1038127/	Geoffrey Rush, \nAnthony LaPaglia, \nSamuel Johnson, \nBarry Otto	/name/nm0001691/,/name/nm0001439/,/name/nm0426170/,/name/nm0653222/	left_only
9	$ Dollars	NaN	NaN	4400000.0	[{'id': 18, 'name': 'Drama'}, {'id': 80, 'name': 'Crime'}, {'id': 35, 'name': 'Comedy'}]	121.0	A bank security expert plots with a call girl to rob the safety deposit boxes of three very different criminals from a high-tech bank in Hamburg.	R	en	6.6	$dollars	[{'iso_3166_1': 'US', 'name': 'United States of America'}]	tt0068152	[{'name': 'Columbia Pictures Corporation', 'id': 441}, {'name': 'Worldwide', 'id': 55873}, {'name': 'Pan', 'id': 55874}]	1971-12-17	1971.0	[{'cast_id': 1, 'character': 'Joe Collins', 'credit_id': '52fe44929251416c910155cb', 'gender': 2, 'id': 6449, 'name': 'Warren Beatty', 'order': 0, 'profile_path': '/1fsYRe1WhIohbfk8qHmjMcuCXeJ.jpg'}, {'cast_id': 2, 'character': 'Dawn Divine', 'credit_id': '52fe44929251416c910155cf', 'gender': 1, 'id': 18892, 'name': 'Goldie Hawn', 'order': 1, 'profile_path': '/6uCoDnRMwk9zGUYnuI2VPvDUjU6.jpg'}, {'cast_id': 3, 'character': 'Mr. Kessel', 'credit_id': '52fe44929251416c910155d3', 'gender': 2, 'id': 9908, 'name': 'Gert Fröbe', 'order': 2, 'profile_path': '/eMXyEZXTWAcfUXPACYfG0pka0Id.jpg'}, {'cast_id': 4, 'character': 'Attorney', 'credit_id': '52fe44929251416c910155d7', 'gender': 2, 'id': 5255, 'name': 'Robert Webber', 'order': 3, 'profile_path': '/mg6SHDi5bi9C7pUwH14ZXxTnR7M.jpg'}, {'cast_id': 5, 'character': 'Sarge', 'credit_id': '52fe44929251416c910155db', 'gender': 2, 'id': 14847, 'name': 'Scott Brady', 'order': 4, 'profile_path': '/2JlQcMIbISvcQjtO4iIB1yZSqwW.jpg'}, {'cast_id': 8, 'character': 'Candy Man', 'credit_id': '54dd58dec3a368454d000827', 'gender': 2, 'id': 22623, 'name': 'Arthur Brauss', 'order': 5, 'profile_path': '/tSMGcGiM0BCZqVPEHfrPVF4rU4d.jpg'}, {'cast_id': 9, 'character': 'Major', 'credit_id': '54dd58ef925141195000081e', 'gender': 0, 'id': 1426629, 'name': 'Robert Stiles', 'order': 6, 'profile_path': None}, {'cast_id': 10, 'character': 'Granich', 'credit_id': '54dd5904c3a36854460002f5', 'gender': 2, 'id': 26517, 'name': 'Wolfgang Kieling', 'order': 7, 'profile_path': '/7kkIf5WtM3ickLQglG9PoqeWn2e.jpg'}, {'cast_id': 16, 'character': 'Helga', 'credit_id': '58b602d8925141260a001031', 'gender': 1, 'id': 40974, 'name': 'Christiane Maybach', 'order': 8, 'profile_path': '/bBsjTvhSjQdhiKwVfkdD3CeVDEA.jpg'}, {'cast_id': 17, 'character': 'Bodyguard (as Robert Herron)', 'credit_id': '58b61c6a92514122e0002376', 'gender': 0, 'id': 1016007, 'name': 'Bob Herron', 'order': 9, 'profile_path': None}, {'cast_id': 18, 'character': 'Karl', 'credit_id': '58b61c8d9251412ab1001f09', 'gender': 0, 'id': 1673380, 'name': 'Hans Hutter', 'order': 10, 'profile_path': None}, {'cast_id': 19, 'character': 'Berta', 'credit_id': '58b61cb79251416129004b8d', 'gender': 0, 'id': 1767429, 'name': 'Monica Stender', 'order': 11, 'profile_path': None}, {'cast_id': 20, 'character': 'Bruno', 'credit_id': '58b61ccfc3a3687be6002630', 'gender': 2, 'id': 26334, 'name': 'Horst Hesslein', 'order': 12, 'profile_path': None}, {'cast_id': 21, 'character': 'Furcoat', 'credit_id': '58b61d00c3a36806780021f4', 'gender': 0, 'id': 1171585, 'name': 'Wolfgang Kuhlmann', 'order': 13, 'profile_path': None}, {'cast_id': 22, 'character': 'Knifeman (as Klaus Tschichan)', 'credit_id': '58b61d25925141260a0020e6', 'gender': 0, 'id': 1350708, 'name': 'Klaus Schichan', 'order': 14, 'profile_path': None}]	[{'credit_id': '52fe44929251416c910155e1', 'department': 'Directing', 'gender': 2, 'id': 3632, 'job': 'Director', 'name': 'Richard Brooks', 'profile_path': '/2xTXd8iz1kKrH0sV4KFuEwZs62O.jpg'}, {'credit_id': '52fe44929251416c910155e7', 'department': 'Writing', 'gender': 2, 'id': 3632, 'job': 'Writer', 'name': 'Richard Brooks', 'profile_path': '/2xTXd8iz1kKrH0sV4KFuEwZs62O.jpg'}, {'credit_id': '54dd594fc3a3684558000844', 'department': 'Sound', 'gender': 2, 'id': 13301, 'job': 'Music', 'name': 'Quincy Jones', 'profile_path': '/mV7hXHeUSXV7KZEfsxJ8lMrKpAt.jpg'}, {'credit_id': '572add60c3a36848010013c4', 'department': 'Camera', 'gender': 2, 'id': 45717, 'job': 'Director of Photography', 'name': 'Petrus R. Schlömp', 'profile_path': None}, {'credit_id': '54dd598a925141194b000888', 'department': 'Editing', 'gender': 0, 'id': 67894, 'job': 'Editor', 'name': 'George Grenville', 'profile_path': None}, {'credit_id': '54dd596a92514103bb000354', 'department': 'Production', 'gender': 0, 'id': 1293412, 'job': 'Producer', 'name': 'M.J. Frankovich', 'profile_path': '/72g1p035ipyZaV3NglZFgtRkaey.jpg'}, {'credit_id': '58b61e319251411d14002a52', 'department': 'Production', 'gender': 0, 'id': 1467196, 'job': 'Unit Manager', 'name': 'Frank Winterstein', 'profile_path': None}, {'credit_id': '58b61e0792514122e00024a8', 'department': 'Sound', 'gender': 0, 'id': 1767430, 'job': 'Music Editor', 'name': 'Ralph Hall', 'profile_path': None}]	Richard Brooks	/name/nm0112218/	Warren Beatty, \nGoldie Hawn, \nGert Fröbe, \nRobert Webber	/name/nm0000886/,/name/nm0000443/,/name/nm0002085/,/name/nm0916434/	left_only

	final_title	final_budget	final_worldwide_boxoffice	final_domestic_boxoffice	final_genres	final_runtime	final_overview	final_certificate	final_original_language	final_rating	final_clean_title	final_production_countries	imdb_id	production_companies	release_date	final_year	cast	crew	director	director_id	star	star_id	_merge
49856	후궁: 제왕의 첩	NaN	NaN	NaN	[{'id': 18, 'name': 'Drama'}]	122.0	Set during the early Joseon Dynasty, the film begins with the queen mother and former concubine (Park Ji-young) in a precarious position of having no blood ties to the childless king (Jung Chan). She schemes to replace him on the throne with his stepbrother and her submissive young son Seong-won (Kim Dong-wook). Indifferent to his mother’s plans, the timid prince falls in love at first sight with Hwa-yeon (Jo Yeo-jeong), an aristocrat’s daughter, who has already found love with Kwon-yoo (Kim Min-joon), a commoner. The king is eventually poisoned to death by the queen mother, who is desperate to be in power. Hwa-yeon is moved to a closely watched humble residence, with the queen mother planning to assassinate Hwa-yeon and her son to secure her position in the palace.	Unrated	ko	5.9	후궁:제왕의첩	[{'iso_3166_1': 'KR', 'name': 'South Korea'}]	tt2544120	[{'name': 'Lotte Entertainment', 'id': 7819}]	2012-06-06	2012.0	[{'cast_id': 28, 'character': 'Hwa-Yeon', 'credit_id': '530df561c3a3685bfb00285f', 'gender': 1, 'id': 556435, 'name': 'Jo Yeo-jeong', 'order': 0, 'profile_path': '/e1a4KlwRzp1jsHxVYjiLtVdrDH9.jpg'}, {'cast_id': 29, 'character': 'Grand Prince Seong-Won', 'credit_id': '530df5ccc3a3685c12002939', 'gender': 2, 'id': 118976, 'name': 'Kim Dong-wook', 'order': 1, 'profile_path': '/mXOe140fwEAJkAkLyWldv8Hs7ux.jpg'}, {'cast_id': 37, 'character': 'Kwon-yoo / Choong-young', 'credit_id': '55ccd662c3a3681bf20001c4', 'gender': 2, 'id': 1257594, 'name': 'Kim Min-joon', 'order': 2, 'profile_path': '/xQd1tqNbLiyJtZF9I8O6KWL9FjR.jpg'}, {'cast_id': 40, 'character': "King's mother", 'credit_id': '57c9b79b9251413de30002f2', 'gender': 1, 'id': 1673497, 'name': 'Park Ji-young', 'order': 3, 'profile_path': '/wrXitjj4YZlUdgqOXXbnqhHKxnw.jpg'}, {'cast_id': 33, 'character': 'Geum-Ok', 'credit_id': '554dadd19251413e4000181a', 'gender': 0, 'id': 1080933, 'name': 'Jo Eun-Ji', 'order': 4, 'profile_path': '/hy0sKZFquiggTmCPmCa9yjPHCpK.jpg'}, {'cast_id': 39, 'character': 'Chief eunuch', 'credit_id': '57b1a2f79251410e95001762', 'gender': 2, 'id': 1293080, 'name': 'Lee Kyoung-young', 'order': 5, 'profile_path': '/aJT9impAPJwixrvL7EjRhtgd4v0.jpg'}, {'cast_id': 36, 'character': "Hwayeon's father", 'credit_id': '55be0594c3a36865260041d9', 'gender': 0, 'id': 1239677, 'name': 'Ahn Suk-hwan', 'order': 6, 'profile_path': '/wms1Fpki825XbOM8drFx9n5NpAv.jpg'}]	[{'credit_id': '53401d410e0a2679ad00009d', 'department': 'Crew', 'gender': 0, 'id': 1299478, 'job': 'Lighting Camera', 'name': 'Daehui Kang', 'profile_path': None}, {'credit_id': '562d4da8c3a3681b4b008174', 'department': 'Writing', 'gender': 0, 'id': 232409, 'job': 'Screenplay', 'name': 'Mee-jeung Kim', 'profile_path': '/zrpfwOOijjvzDGa0A0onzIcKBd2.jpg'}, {'credit_id': '53038eed925141219b5b14e8', 'department': 'Writing', 'gender': 0, 'id': 1294139, 'job': 'Screenplay', 'name': 'Yunjeong Hwang', 'profile_path': None}, {'credit_id': '53038ef992514161a232ad0d', 'department': 'Production', 'gender': 0, 'id': 1294140, 'job': 'Producer', 'name': 'Park Seongil', 'profile_path': None}, {'credit_id': '53038f05925141218f5ff951', 'department': 'Crew', 'gender': 0, 'id': 1294141, 'job': 'Cinematography', 'name': 'Giseok Hwang', 'profile_path': None}, {'credit_id': '53038f2492514121925e765d', 'department': 'Sound', 'gender': 0, 'id': 1293612, 'job': 'Original Music Composer', 'name': 'Yeonguk Jo', 'profile_path': None}, {'credit_id': '53038f3292514121a4622605', 'department': 'Costume & Make-Up', 'gender': 0, 'id': 1293613, 'job': 'Costume Design', 'name': 'Sanggyeong Jo', 'profile_path': None}, {'credit_id': '53038f3b92514121955b4855', 'department': 'Costume & Make-Up', 'gender': 0, 'id': 1294144, 'job': 'Costume Design', 'name': 'Mira Yun', 'profile_path': None}, {'credit_id': '5551151fc3a3687f63007188', 'department': 'Directing', 'gender': 2, 'id': 132177, 'job': 'Director', 'name': 'Kim Dae-seung', 'profile_path': '/upTNQBHwfy9xGaOKKqDrCBTxLfA.jpg'}, {'credit_id': '5551152ac3a368436d001091', 'department': 'Writing', 'gender': 2, 'id': 132177, 'job': 'Screenplay', 'name': 'Kim Dae-seung', 'profile_path': '/upTNQBHwfy9xGaOKKqDrCBTxLfA.jpg'}]	Dae-seung Kim	/name/nm0453413/	Cho Yeo-jeong, \nDong-wook Kim, \nMin-Joon Kim, \nPark Ji-young	/name/nm1856097/,/name/nm1118612/,/name/nm2024084/,/name/nm4735633/	left_only
49857	후회하지 않아	NaN	NaN	14620.0	[{'id': 18, 'name': 'Drama'}, {'id': 10749, 'name': 'Romance'}]	113.0	Sumin is an orphan trying to balance work in a factory with study at an art college and an evening job. One night, a rich young businessman makes an advance on him during one of his driving jobs. They meet again the next day: it is during a round of redundancy cuts at the factory where Sumin refuses an attempt by a man (who is in fact the boss' son Jaemin) to save his job. Eventually, Sumin is seduced into working as a prostitute in an up-market boy-brothel as Jaemin's obsession with him grows, leaving Jaemin helpless in the face of his overwhelming desire. This is a film of bold sexuality, where unexpected passion, desire and misunderstandings wreak havoc of an operatic intensity.	R	ko	6.4	후회하지않아	[{'iso_3166_1': 'KR', 'name': 'South Korea'}]	tt0996948	[{'name': 'Generation Blue Films', 'id': 79409}]	2006-11-16	2006.0	[{'cast_id': 4, 'character': 'Song Jae-min', 'credit_id': '578c40879251410824001372', 'gender': 2, 'id': 110388, 'name': 'Kim Nam-gil', 'order': 2, 'profile_path': '/beafwFkUeyXCakywsTNpVb0b4hm.jpg'}, {'cast_id': 5, 'character': 'Lee Su-min', 'credit_id': '578c40c39251417aca00ceff', 'gender': 2, 'id': 1652535, 'name': 'Lee Young-Hoon', 'order': 3, 'profile_path': '/oq7ITPpmCd5TV8r8jvXCknk7oMz.jpg'}, {'cast_id': 6, 'character': 'Ga-ram', 'credit_id': '58385cf79251414cb9016a5f', 'gender': 2, 'id': 118976, 'name': 'Kim Dong-wook', 'order': 4, 'profile_path': '/mXOe140fwEAJkAkLyWldv8Hs7ux.jpg'}, {'cast_id': 8, 'character': 'Madame', 'credit_id': '59154c90c3a3683a9301847b', 'gender': 2, 'id': 1420814, 'name': 'Jung Seung-kil', 'order': 5, 'profile_path': None}]	[{'credit_id': '59154ca0925141583c019146', 'department': 'Directing', 'gender': 2, 'id': 1030914, 'job': 'Director', 'name': 'Leesong Hee-il', 'profile_path': '/hY5C9atZTM9jIdnpv0yWuJ3ny7p.jpg'}, {'credit_id': '59154caac3a3683a93018491', 'department': 'Writing', 'gender': 2, 'id': 1030914, 'job': 'Writer', 'name': 'Leesong Hee-il', 'profile_path': '/hY5C9atZTM9jIdnpv0yWuJ3ny7p.jpg'}]	Hee-il Leesong	/name/nm1276328/	Nam-gil Kim, \nYoung-hoon Lee, \nHyeon-cheol Jo, \nDong-wook Kim	/name/nm2339825/,/name/nm2608040/,/name/nm2604957/,/name/nm1118612/	left_only
49858	龍在江湖	NaN	NaN	NaN	[{'id': 10769, 'name': 'Foreign'}]	112.0	A low level gangster in Hong Kong gains new respect after saving a boss's life in a gang fight. Despite his wife's death in this attack, he appears to be moving up in the Triad family until he discovers the other bosses are not looking out for him when he is double crossed and the gangster he previously hospitalized in the gang fight comes back for revenge.	NaN	cn	7.0	龍在江湖	[]	tt0165998	[]	1998-07-01	1998.0	[{'cast_id': 17, 'character': 'Wai Cheung-Dee', 'credit_id': '52fe4961c3a36847f81971e7', 'gender': 2, 'id': 25246, 'name': 'Andy Lau', 'order': 0, 'profile_path': '/8LCbwZJhjJRew59dJ7xSqyozVWf.jpg'}, {'cast_id': 3, 'character': 'Sandy Leung', 'credit_id': '52fe4961c3a36847f81971af', 'gender': 0, 'id': 65938, 'name': 'Gigi Leung', 'order': 1, 'profile_path': '/sx6eq3Zpi1FyEGW8IAWWKVi4vFg.jpg'}, {'cast_id': 4, 'character': 'Ruby Kwan', 'credit_id': '52fe4961c3a36847f81971b3', 'gender': 1, 'id': 227804, 'name': 'Suki Kwan', 'order': 2, 'profile_path': '/b8suIKTFSxLm4wDdYyXUXUrNqg8.jpg'}, {'cast_id': 5, 'character': 'Prince', 'credit_id': '52fe4961c3a36847f81971b7', 'gender': 2, 'id': 65197, 'name': 'Mark Cheng', 'order': 3, 'profile_path': '/dOX91UKJe1ZazravuzjBSpQG82k.jpg'}, {'cast_id': 6, 'character': 'Michael', 'credit_id': '52fe4961c3a36847f81971bb', 'gender': 2, 'id': 21914, 'name': 'Alex Fong Chung-Sun', 'order': 4, 'profile_path': '/lqSnU4hYkr8VyNnG03mMrmB9dwl.jpg'}, {'cast_id': 7, 'character': 'David', 'credit_id': '52fe4961c3a36847f81971bf', 'gender': 0, 'id': 227805, 'name': 'Joe Ma', 'order': 5, 'profile_path': '/ct2ZMpYGSeyWxsVfb3RIpNDC8u1.jpg'}, {'cast_id': 8, 'character': 'Skinny', 'credit_id': '52fe4961c3a36847f81971c3', 'gender': 0, 'id': 74193, 'name': 'Sam Lee', 'order': 6, 'profile_path': '/peBEATyBMxLnbqdg9DLBZVyJXkY.jpg'}, {'cast_id': 9, 'character': 'Fai', 'credit_id': '52fe4961c3a36847f81971c7', 'gender': 0, 'id': 65943, 'name': 'Chi Hung Ng', 'order': 7, 'profile_path': None}, {'cast_id': 10, 'character': 'Crazy Ball', 'credit_id': '52fe4961c3a36847f81971cb', 'gender': 0, 'id': 227806, 'name': 'Ben Ng', 'order': 8, 'profile_path': '/x62jhwD0uue1jhxX02Q7PbS7gOm.jpg'}, {'cast_id': 11, 'character': 'Uncle Hei', 'credit_id': '52fe4961c3a36847f81971cf', 'gender': 2, 'id': 83358, 'name': 'Michael Chan Wai-Man', 'order': 9, 'profile_path': '/pApINF6vLdiufL5T73yeYkd6jHv.jpg'}, {'cast_id': 12, 'character': 'Uncle Pao', 'credit_id': '52fe4961c3a36847f81971d3', 'gender': 2, 'id': 122816, 'name': 'Lee Siu-Kei', 'order': 10, 'profile_path': '/yEZS8hArr57X9as49TkxGaJXeW8.jpg'}, {'cast_id': 13, 'character': 'Uncle Fa', 'credit_id': '52fe4961c3a36847f81971d7', 'gender': 0, 'id': 112988, 'name': 'Tian-lin Wang', 'order': 11, 'profile_path': None}, {'cast_id': 14, 'character': 'Cindy', 'credit_id': '52fe4961c3a36847f81971db', 'gender': 0, 'id': 227807, 'name': 'Angie Cheung', 'order': 12, 'profile_path': '/5iAGeVHd3DpXExhycBle0wdDu9a.jpg'}, {'cast_id': 15, 'character': 'Judge', 'credit_id': '52fe4961c3a36847f81971df', 'gender': 2, 'id': 64662, 'name': 'Dennis Chan', 'order': 13, 'profile_path': '/qZiaEH1JJt8c0WUPJl9gqArGT2P.jpg'}, {'cast_id': 16, 'character': 'Fifi', 'credit_id': '52fe4961c3a36847f81971e3', 'gender': 0, 'id': 227808, 'name': 'Danise Chan', 'order': 14, 'profile_path': None}]	[{'credit_id': '52fe4961c3a36847f81971ed', 'department': 'Directing', 'gender': 2, 'id': 548474, 'job': 'Director', 'name': 'Wong Jing', 'profile_path': '/asZClP70V7W8zlFDzAzuQFGBZtC.jpg'}]	Jing Wong	/name/nm0939147/	Andy Lau, \nGigi Leung, \nSuki Kwan, \nMark Cheng	/name/nm0490489/,/name/nm0504942/,/name/nm0477105/,/name/nm0155599/	left_only
49859	琉璃樽	NaN	NaN	NaN	[{'id': 12, 'name': 'Adventure'}, {'id': 28, 'name': 'Action'}, {'id': 35, 'name': 'Comedy'}, {'id': 10749, 'name': 'Romance'}]	121.0	When Ah Bu, a girl from a small fishing town in Taiwan, finds a glass bottle with a romantic message, she travels to Hong Kong to find her prince charming. As it turns out, her prince charming, Albert, happens to be gay. But all is not lost when Ah Bu meets the dashing Chi Wu. Meanwhile, Ah Bu's boyfriend from Taiwan comes looking for her, as the action and romance follow Ah Bu back to Taiwan.	PG-13	cn	6.0	琉璃樽	[{'iso_3166_1': 'HK', 'name': 'Hong Kong'}]	tt0184526	[{'name': 'Golden Harvest Pictures', 'id': 969}]	1999-02-12	1999.0	[{'cast_id': 1, 'character': 'C.N. Chan', 'credit_id': '52fe43d89251416c75020493', 'gender': 2, 'id': 18897, 'name': 'Jackie Chan', 'order': 0, 'profile_path': '/tEJazyboCJcsvxnhKH3Hf33Bmgj.jpg'}, {'cast_id': 2, 'character': 'Bu', 'credit_id': '52fe43d89251416c75020497', 'gender': 1, 'id': 21911, 'name': 'Shu Qi', 'order': 1, 'profile_path': '/kmTErFq6lKQww2Yk9AfpR2Q5YWx.jpg'}, {'cast_id': 3, 'character': 'Albert', 'credit_id': '52fe43d89251416c7502049b', 'gender': 2, 'id': 1337, 'name': 'Tony Leung Chiu-Wai', 'order': 2, 'profile_path': '/xSEwMBLHdiKjyG4YVCsjpaT5fgD.jpg'}, {'cast_id': 14, 'character': 'L.W. Lo', 'credit_id': '541da7f90e0a2612460093c6', 'gender': 0, 'id': 931174, 'name': 'Emil Chow', 'order': 3, 'profile_path': '/iB3clq9RFG4odnyBXG497Gv7bWZ.jpg'}, {'cast_id': 19, 'character': 'Alan', 'credit_id': '54dbbe8ac3a3682f2400207c', 'gender': 0, 'id': 134686, 'name': 'Bradley James Allan', 'order': 4, 'profile_path': '/pSOkpEcVF6sXnXMPQaws5j7AZpO.jpg'}, {'cast_id': 20, 'character': 'Long-Yi', 'credit_id': '54dbbea4925141619b00213e', 'gender': 2, 'id': 64496, 'name': 'Richie Ren', 'order': 5, 'profile_path': '/7hiyjKWSfTh8GplXX9mqgl5F24U.jpg'}, {'cast_id': 21, 'character': "Lo's Bodyguard", 'credit_id': '54dbbeb5c3a3681237002334', 'gender': 2, 'id': 70690, 'name': 'Ken Lo', 'order': 6, 'profile_path': '/3cxY30w6S6hraBUpCtY7S8PQhDq.jpg'}, {'cast_id': 24, 'character': "Bu's father", 'credit_id': '56f7b9b3c3a3686a5c0064a0', 'gender': 0, 'id': 974461, 'name': 'Chan Chung-Yung', 'order': 7, 'profile_path': '/wkpFVREWECzqKSmfN5KVgqt4A7j.jpg'}, {'cast_id': 23, 'character': "Bu's Mother", 'credit_id': '54dbbecb925141619e0023e0', 'gender': 0, 'id': 103598, 'name': 'Elaine Jin', 'order': 8, 'profile_path': '/vxJzPWCcRQ2nLiHfZmYwPTS3KEr.jpg'}, {'cast_id': 15, 'character': 'Pretty girl at seaside', 'credit_id': '548b4a43c3a36856e80003f8', 'gender': 0, 'id': 105421, 'name': 'Jo Kuk', 'order': 9, 'profile_path': '/2RN8Ubr1UeenZKDqg1uIBUdqixG.jpg'}, {'cast_id': 16, 'character': 'Airport Pickpocket', 'credit_id': '548b4dc59251416eb200049a', 'gender': 1, 'id': 88495, 'name': 'Sandra Ng Kwun-Yu', 'order': 10, 'profile_path': '/hIQWKC82xAQHvO5Cm4J31ZZLEEh.jpg'}, {'cast_id': 17, 'character': 'Xiao Jun', 'credit_id': '54a4e2089251414e2800e48c', 'gender': 0, 'id': 120419, 'name': 'Annie Wu', 'order': 11, 'profile_path': '/qcqEz2KHWUpjFJnO12fMidSFIU4.jpg'}, {'cast_id': 25, 'character': "Howie's bodyguard", 'credit_id': '573f0355c3a36839df0021a2', 'gender': 0, 'id': 1123830, 'name': 'William Chan Yuk-Choh', 'order': 12, 'profile_path': None}, {'cast_id': 26, 'character': 'Michele', 'credit_id': '576a0ab79251416e43001134', 'gender': 0, 'id': 1639507, 'name': 'Jacqueline Li', 'order': 13, 'profile_path': None}, {'cast_id': 27, 'character': 'Elaine', 'credit_id': '576a0ac1c3a36829a900125e', 'gender': 0, 'id': 987139, 'name': 'Eileen Tung', 'order': 14, 'profile_path': '/8Lvsv6C90LHYrYDLJ613seT1RMf.jpg'}, {'cast_id': 28, 'character': 'Policeman with dog', 'credit_id': '591041f39251414e8902fdcf', 'gender': 2, 'id': 57607, 'name': 'Stephen Chow', 'order': 15, 'profile_path': '/aizTZF5vHoOg6Ck7Nq5X65ULYoa.jpg'}]	[{'credit_id': '52fe43d89251416c750204c3', 'department': 'Writing', 'gender': 2, 'id': 18897, 'job': 'Screenplay', 'name': 'Jackie Chan', 'profile_path': '/tEJazyboCJcsvxnhKH3Hf33Bmgj.jpg'}, {'credit_id': '52fe43d89251416c750204b1', 'department': 'Production', 'gender': 2, 'id': 18897, 'job': 'Producer', 'name': 'Jackie Chan', 'profile_path': '/tEJazyboCJcsvxnhKH3Hf33Bmgj.jpg'}, {'credit_id': '52fe43d89251416c750204ab', 'department': 'Production', 'gender': 2, 'id': 46323, 'job': 'Producer', 'name': 'Raymond Chow', 'profile_path': '/zAIthSX6xZoaj1J09Uv6JzagKWP.jpg'}, {'credit_id': '52fe43d89251416c750204d5', 'department': 'Editing', 'gender': 2, 'id': 63574, 'job': 'Editor', 'name': 'Cheung Ka-Fai', 'profile_path': None}, {'credit_id': '52fe43d89251416c750204b7', 'department': 'Writing', 'gender': 0, 'id': 63577, 'job': 'Author', 'name': 'Yiu Fai Lo', 'profile_path': None}, {'credit_id': '52fe43d89251416c750204bd', 'department': 'Writing', 'gender': 2, 'id': 65934, 'job': 'Screenplay', 'name': 'Vincent Kok', 'profile_path': '/mTtFWZKHYSKNaS7GHSuVho4THp.jpg'}, {'credit_id': '52fe43d89251416c750204a5', 'department': 'Directing', 'gender': 2, 'id': 65934, 'job': 'Director', 'name': 'Vincent Kok', 'profile_path': '/mTtFWZKHYSKNaS7GHSuVho4THp.jpg'}, {'credit_id': '52fe43d89251416c750204c9', 'department': 'Sound', 'gender': 0, 'id': 67890, 'job': 'Music', 'name': 'Dang-Yi Wong', 'profile_path': None}, {'credit_id': '52fe43d89251416c750204cf', 'department': 'Camera', 'gender': 0, 'id': 67891, 'job': 'Director of Photography', 'name': 'Man Po Cheung', 'profile_path': None}]	Vincent Kok	/name/nm0463674/	Jackie Chan, \nShu Qi, \nTony Chiu-Wai Leung, \nEmil Chau	/name/nm0000329/,/name/nm0795517/,/name/nm0504897/,/name/nm0154235/	left_only
49860	０課の女　赤い手錠	NaN	NaN	NaN	[{'id': 53, 'name': 'Thriller'}, {'id': 28, 'name': 'Action'}, {'id': 80, 'name': 'Crime'}, {'id': 18, 'name': 'Drama'}]	88.0	Agent Zero (Miki Sugimoto) is a cop that uses her own methods for dealing with criminals. After she unlawfully kills a rapist in a violent fashion, she is sent to prison and stripped of her badge. But very soon after, a rich politician's daughter is kidnapped by a ruthless gang. Agent Zero is let out of prison with the mission of going undercover to find the politician's daughter and return her safely. Using her deadly red handcuffs, she disposes of the criminals one by one.	Unrated	ja	6.7	０課の女　赤い手錠	[{'iso_3166_1': 'JP', 'name': 'Japan'}]	tt0283693	[{'name': 'Toei Company', 'id': 9255}]	1974-05-21	1974.0	[{'cast_id': 4, 'character': 'Rei, Zero woman', 'credit_id': '52fe4690c3a368484e0978e1', 'gender': 0, 'id': 109691, 'name': 'Miki Sugimoto', 'order': 0, 'profile_path': '/5tTSr7DOCUinZ08jTW80srtwDDG.jpg'}, {'cast_id': 5, 'character': 'Yoshihide', 'credit_id': '52fe4690c3a368484e0978e5', 'gender': 2, 'id': 86247, 'name': 'Eiji Gô', 'order': 1, 'profile_path': None}, {'cast_id': 6, 'character': 'Nagumo', 'credit_id': '52fe4690c3a368484e0978e9', 'gender': 2, 'id': 10071, 'name': 'Tetsurō Tamba', 'order': 2, 'profile_path': '/lrWc0QjdAaP1VOWhwzczakdaEq.jpg'}, {'cast_id': 7, 'character': 'Kusaka', 'credit_id': '52fe4690c3a368484e0978ed', 'gender': 0, 'id': 120348, 'name': 'Hideo Murota', 'order': 3, 'profile_path': '/vDoABc3QM8MYOrxQLn0xfUl3vs5.jpg'}, {'cast_id': 8, 'character': 'Sesum, the Madame', 'credit_id': '52fe4690c3a368484e0978f1', 'gender': 1, 'id': 236092, 'name': 'Yôko Mihara', 'order': 4, 'profile_path': None}, {'cast_id': 9, 'character': 'Saburô Seki', 'credit_id': '52fe4690c3a368484e0978f5', 'gender': 0, 'id': 454568, 'name': 'Ichirô Araki', 'order': 5, 'profile_path': None}, {'cast_id': 10, 'character': 'Tooru Inaba', 'credit_id': '52fe4690c3a368484e0978f9', 'gender': 0, 'id': 234450, 'name': 'Seiji Endô', 'order': 6, 'profile_path': None}, {'cast_id': 11, 'character': 'Tani / Police', 'credit_id': '52fe4690c3a368484e0978fd', 'gender': 2, 'id': 138748, 'name': 'Rokkô Toura', 'order': 7, 'profile_path': None}]	[{'credit_id': '52fe4690c3a368484e0978d1', 'department': 'Directing', 'gender': 0, 'id': 109690, 'job': 'Director', 'name': 'Yukio Noda', 'profile_path': None}, {'credit_id': '52fe4690c3a368484e0978dd', 'department': 'Writing', 'gender': 2, 'id': 228553, 'job': 'Writer', 'name': 'Hirô Matsuda', 'profile_path': None}, {'credit_id': '52fe4690c3a368484e0978d7', 'department': 'Writing', 'gender': 0, 'id': 236091, 'job': 'Writer', 'name': 'Fumio Kônami', 'profile_path': None}]	Yukio Noda	/name/nm0633805/	Miki Sugimoto, \nEiji Gô, \nTetsurô Tanba, \nHideo Murota	/name/nm0999315/,/name/nm0323530/,/name/nm0848533/,/name/nm0605712/	left_only
49861	１リットルの涙	NaN	NaN	NaN	[{'id': 18, 'name': 'Drama'}]	98.0	15-year-old Ikeuchi Aya was an ordinary girl, the daughter of a family who works at a tofu shop, and a soon-to-be high schooler. However, odd things have been happening to Aya lately. She has been falling down often and walks strange. Her mother, Shioka, takes Aya to see the doctor. How will Aya react when told about her disease? And how will Aya live from now on?	NaN	ja	7.7	１リットルの涙	[{'iso_3166_1': 'JP', 'name': 'Japan'}]	tt0494724	[{'name': 'TOEI', 'id': 7260}]	2005-02-05	2005.0	[{'cast_id': 3, 'character': '', 'credit_id': '52fe45bfc3a36847f80d82b5', 'gender': 1, 'id': 125941, 'name': 'Yoshimi Ashikawa', 'order': 0, 'profile_path': None}, {'cast_id': 4, 'character': 'Aya Kito', 'credit_id': '52fe45bfc3a36847f80d82b9', 'gender': 0, 'id': 125942, 'name': 'Asae Oonishi', 'order': 1, 'profile_path': None}, {'cast_id': 5, 'character': 'Hiroshi Mizuno', 'credit_id': '52fe45bfc3a36847f80d82bd', 'gender': 2, 'id': 125943, 'name': 'Naohito Fujiki', 'order': 2, 'profile_path': '/88ceM9xyfxdpJTNt6rLUhL9nl8Z.jpg'}, {'cast_id': 6, 'character': 'Keita Nakahara', 'credit_id': '52fe45bfc3a36847f80d82c1', 'gender': 0, 'id': 125944, 'name': 'Ryô Hashizume', 'order': 3, 'profile_path': '/ngr0HPBIiqTPPOrtYUqBKDQmE4h.jpg'}, {'cast_id': 7, 'character': 'Mizuo Ikeuchi', 'credit_id': '52fe45bfc3a36847f80d82c5', 'gender': 2, 'id': 97320, 'name': 'Takanori Jinnai', 'order': 4, 'profile_path': '/nfQUSM0VVQv79h8QXrtLXF5NcGd.jpg'}, {'cast_id': 8, 'character': 'Madoka Fujimura', 'credit_id': '52fe45bfc3a36847f80d82c9', 'gender': 0, 'id': 83926, 'name': 'Kazuko Katô', 'order': 5, 'profile_path': None}, {'cast_id': 9, 'character': 'Mari Sugiura', 'credit_id': '52fe45bfc3a36847f80d82cd', 'gender': 0, 'id': 125945, 'name': 'Saori Koide', 'order': 6, 'profile_path': '/3YjtMZiZx6cwsQ4ZJNgt3JRmWLr.jpg'}, {'cast_id': 10, 'character': '', 'credit_id': '52fe45bfc3a36847f80d82d1', 'gender': 0, 'id': 125946, 'name': 'Yoneko Matsukane', 'order': 7, 'profile_path': '/crhTojbcjXs9RxdgxbY49JQltuP.jpg'}, {'cast_id': 11, 'character': 'Saki Matsumura', 'credit_id': '52fe45bfc3a36847f80d82d5', 'gender': 0, 'id': 125947, 'name': 'Kana Matsumoto', 'order': 8, 'profile_path': None}, {'cast_id': 12, 'character': 'Yuji Kawamoto', 'credit_id': '52fe45bfc3a36847f80d82d9', 'gender': 2, 'id': 79037, 'name': 'Kenichi Matsuyama', 'order': 9, 'profile_path': '/8V1tX3womN0KOcX9FjYPLrGstKn.jpg'}, {'cast_id': 13, 'character': 'Rika Ikeuchi', 'credit_id': '52fe45bfc3a36847f80d82dd', 'gender': 0, 'id': 125948, 'name': 'Ani Miyoshi', 'order': 10, 'profile_path': None}, {'cast_id': 14, 'character': 'Kohei Onda', 'credit_id': '52fe45bfc3a36847f80d82e1', 'gender': 0, 'id': 125949, 'name': 'Momosuke Mizutani', 'order': 11, 'profile_path': None}, {'cast_id': 17, 'character': 'Hiroki Ikeuchi', 'credit_id': '52fe45bfc3a36847f80d82ed', 'gender': 0, 'id': 125951, 'name': 'Yuma Sanada', 'order': 14, 'profile_path': None}]	[{'credit_id': '52fe45bfc3a36847f80d82ab', 'department': 'Directing', 'gender': 0, 'id': 125939, 'job': 'Director', 'name': 'Riki Okamura', 'profile_path': None}, {'credit_id': '52fe45bfc3a36847f80d82b1', 'department': 'Writing', 'gender': 0, 'id': 125940, 'job': 'Writer', 'name': 'Aya Kito', 'profile_path': None}]	NaN	NaN	NaN	NaN	left_only
49862	１３号待避線より　その護送車を狙え	NaN	NaN	NaN	[{'id': 28, 'name': 'Action'}, {'id': 80, 'name': 'Crime'}]	79.0	A sharpshooter kills two prisoners in a police van at night. The guard on the van is suspended for six months; he's Tamon, an upright, modest man. He begins his own investigation into the murders. Who were the victims, who are their relatives and girlfriends, who else was on the van that night? As he doggedly investigates, others die, coincidences occur, and several leads take him to the Hamaju Agency, which may be supplying call girls. Its owner is in jail, his daughter, the enigmatic Yuko, keeps turning up where Tamon goes. Tamon believes he can awaken good in people, but has he met his match? Will he solve the murders or be the next victim? And who is Akiba?	Not Rated	ja	5.4	１３号待避線より　その護送車を狙え	[{'iso_3166_1': 'JP', 'name': 'Japan'}]	tt0054325	[{'name': 'Nikkatsu', 'id': 955}]	1960-01-27	1960.0	[{'cast_id': 7, 'character': 'Daijiro Tamon', 'credit_id': '52fe4845c3a368484e0f07bd', 'gender': 0, 'id': 232078, 'name': 'Michitaro Mizushima', 'order': 0, 'profile_path': None}, {'cast_id': 8, 'character': 'Tsunako Ando', 'credit_id': '52fe4845c3a368484e0f07c1', 'gender': 0, 'id': 229404, 'name': 'Mari Shiraki', 'order': 1, 'profile_path': None}, {'cast_id': 9, 'character': 'Yuko Hamashima', 'credit_id': '52fe4845c3a368484e0f07c5', 'gender': 1, 'id': 111235, 'name': 'Misako Watanabe', 'order': 2, 'profile_path': None}, {'cast_id': 10, 'character': 'Jube Hamashima', 'credit_id': '52fe4845c3a368484e0f07c9', 'gender': 0, 'id': 72391, 'name': 'Shinsuke Ashida', 'order': 3, 'profile_path': None}, {'cast_id': 11, 'character': 'Goro Kashima', 'credit_id': '52fe4845c3a368484e0f07cd', 'gender': 0, 'id': 142454, 'name': 'Shoichi Ozawa', 'order': 4, 'profile_path': '/ht4yEUx9l4P9ckxu9zJPTjCDqvH.jpg'}, {'cast_id': 12, 'character': 'Kuji', 'credit_id': '52fe4845c3a368484e0f07d1', 'gender': 0, 'id': 226747, 'name': 'Ryôhei Uchida', 'order': 5, 'profile_path': None}, {'cast_id': 13, 'character': 'Akahori', 'credit_id': '52fe4845c3a368484e0f07d5', 'gender': 2, 'id': 83640, 'name': 'Tôru Abe', 'order': 6, 'profile_path': '/1pApwHFzrWUbX6BvoMRJ9E9edhc.jpg'}, {'cast_id': 14, 'character': 'Captain Takamura', 'credit_id': '52fe4845c3a368484e0f07d9', 'gender': 0, 'id': 1093067, 'name': 'Tatsuo Matsushita', 'order': 7, 'profile_path': None}, {'cast_id': 15, 'character': 'Ota', 'credit_id': '52fe4845c3a368484e0f07dd', 'gender': 0, 'id': 551804, 'name': 'Saburo Hiromatsu', 'order': 8, 'profile_path': None}, {'cast_id': 16, 'character': 'Osen', 'credit_id': '52fe4845c3a368484e0f07e1', 'gender': 0, 'id': 1093068, 'name': 'Reiko Arai', 'order': 9, 'profile_path': None}, {'cast_id': 17, 'character': 'Housewife', 'credit_id': '52fe4845c3a368484e0f07e5', 'gender': 0, 'id': 1093069, 'name': 'Toyo Fukuda', 'order': 10, 'profile_path': None}, {'cast_id': 18, 'character': "Merchant's wife", 'credit_id': '52fe4845c3a368484e0f07e9', 'gender': 0, 'id': 65512, 'name': 'Kotoe Hatsui', 'order': 11, 'profile_path': '/k3BhnRlm5HFHHxwpoEaL1e4SXgE.jpg'}, {'cast_id': 19, 'character': 'Masaki', 'credit_id': '52fe4845c3a368484e0f07ed', 'gender': 0, 'id': 1093070, 'name': 'Akira Hisamatsu', 'order': 12, 'profile_path': None}]	[{'credit_id': '52fe4845c3a368484e0f07f3', 'department': 'Writing', 'gender': 2, 'id': 18611, 'job': 'Screenplay', 'name': 'Shinichi Sekizawa', 'profile_path': None}, {'credit_id': '52fe4845c3a368484e0f07b9', 'department': 'Editing', 'gender': 2, 'id': 70632, 'job': 'Editor', 'name': 'Akira Suzuki', 'profile_path': None}, {'credit_id': '52fe4844c3a368484e0f07a1', 'department': 'Directing', 'gender': 2, 'id': 82461, 'job': 'Director', 'name': 'Seijun Suzuki', 'profile_path': '/fGZPvvEYaO1RLdW4PEcYp3IJcOW.jpg'}, {'credit_id': '52fe4845c3a368484e0f07b3', 'department': 'Crew', 'gender': 0, 'id': 554992, 'job': 'Cinematography', 'name': 'Shigeyoshi Mine', 'profile_path': None}, {'credit_id': '52fe4844c3a368484e0f07a7', 'department': 'Writing', 'gender': 0, 'id': 563708, 'job': 'Story', 'name': 'Kazuo Shimada', 'profile_path': None}, {'credit_id': '52fe4845c3a368484e0f07ad', 'department': 'Sound', 'gender': 0, 'id': 1093066, 'job': 'Original Music Composer', 'name': 'Koichi Kawabe', 'profile_path': None}]	Seijun Suzuki	/name/nm0840671/	Michitarô Mizushima, \nMisako Watanabe, \nShôichi Ozawa, \nShinsuke Ashida	/name/nm0594702/,/name/nm0913843/,/name/nm0654726/,/name/nm0038951/	left_only
49863	２０世紀少年< 第1章> 終わりの始まり	20000000.0	31244858.0	NaN	[{'id': 878, 'name': 'Science Fiction'}, {'id': 12, 'name': 'Adventure'}, {'id': 9648, 'name': 'Mystery'}]	142.0	In 1969, Kenji, an elementary school kid and his friends built a secret base during their summer holidays. They fantasized that they had to fight villains who were out to conquer the world and wrote them in the Book of Prophecies. Years later in 1997, Kenji becomes a convenience store manager and leads a regular life after giving up his dreams to become a rock star. His boring life is suddenly turned upside down when his old classmate dies mysteriously and an entire family in the neighbourhood disappears. At the same time, a religious cult and its mysterious leader, Friend emerges and a strange chain of events duplicating exactly the events described in the Book of Prophecies follow. Is this the beginning of the end of the world? Who is Friend?	NaN	ja	6.7	２０世紀少年<第1章>終わりの始まり	[{'iso_3166_1': 'JP', 'name': 'Japan'}, {'iso_3166_1': 'TH', 'name': 'Thailand'}]	tt1155705	[{'name': 'Cine Bazar', 'id': 5896}, {'name': 'Toho', 'id': 5897}]	2008-08-19	2008.0	[{'cast_id': 15, 'character': 'Kenji Endô', 'credit_id': '52fe46019251416c91045e63', 'gender': 2, 'id': 81350, 'name': 'Toshiaki Karasawa', 'order': 0, 'profile_path': '/gaoKYnp57eR7DJGviijCmnJKsV.jpg'}, {'cast_id': 17, 'character': 'Yukiji', 'credit_id': '52fe46019251416c91045e67', 'gender': 1, 'id': 81352, 'name': 'Takako Tokiwa', 'order': 2, 'profile_path': '/sfoeSQozRMSVKid0A8dWAd6ghXt.jpg'}, {'cast_id': 18, 'character': 'Yoshitsune', 'credit_id': '52fe46019251416c91045e6b', 'gender': 2, 'id': 46691, 'name': 'Teruyuki Kagawa', 'order': 3, 'profile_path': '/pCOQFnFHPDCtSuYmMT3Q24Yf0SE.jpg'}, {'cast_id': 19, 'character': 'Maruo', 'credit_id': '52fe46019251416c91045e6f', 'gender': 0, 'id': 131106, 'name': 'Hidehiko Ishizuka', 'order': 4, 'profile_path': None}, {'cast_id': 20, 'character': 'Mon-chan', 'credit_id': '52fe46019251416c91045e73', 'gender': 0, 'id': 131107, 'name': 'Takashi Ukaji', 'order': 5, 'profile_path': '/wawHy4VSbKvhl6JOhIXUCGbTMwi.jpg'}, {'cast_id': 21, 'character': 'Keroyon', 'credit_id': '52fe46019251416c91045e77', 'gender': 2, 'id': 70211, 'name': 'Hiroyuki Miyasako', 'order': 6, 'profile_path': '/t5HCiv3wEnWLn3SqcZlmLOJKXki.jpg'}, {'cast_id': 22, 'character': 'Donkey', 'credit_id': '52fe46019251416c91045e7b', 'gender': 2, 'id': 91873, 'name': 'Katsuhisa Namase', 'order': 7, 'profile_path': '/ppbpmLydzWXzuVWbBr46VP3PZeT.jpg'}, {'cast_id': 23, 'character': 'Yamane', 'credit_id': '52fe46019251416c91045e7f', 'gender': 2, 'id': 58449, 'name': 'Fumiyo Kohinata', 'order': 8, 'profile_path': '/nUugr8JH1cmGRPcMFvSQibShojz.jpg'}, {'cast_id': 24, 'character': 'Fukubê', 'credit_id': '52fe46019251416c91045e83', 'gender': 0, 'id': 121716, 'name': 'Kuranosuke Sasaki', 'order': 9, 'profile_path': '/AfqaeQ4yrA3kQsDDoREN9bcUeKb.jpg'}, {'cast_id': 25, 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49864	３－４Ｘ１０月	NaN	NaN	1471.0	[{'id': 80, 'name': 'Crime'}, {'id': 28, 'name': 'Action'}, {'id': 35, 'name': 'Comedy'}]	96.0	Masaki, a baseball player and gas-station attendant, gets into trouble with the local Yakuza and goes to Okinawa to get a gun to defend himself. There he meets Uehara, a tough gangster, who is in serious debt to the yakuza and planning revenge.	Not Rated	ja	6.6	３－４ｘ１０月	[{'iso_3166_1': 'JP', 'name': 'Japan'}]	tt0098967	[{'name': 'Bandai Visual Company', 'id': 528}, {'name': 'Shochiku-Fuji Company', 'id': 6919}]	1990-09-15	1990.0	[{'cast_id': 2, 'character': 'Masaki', 'credit_id': '52fe4522c3a368484e04a661', 'gender': 2, 'id': 20311, 'name': 'Yūrei Yanagi', 'order': 0, 'profile_path': '/nLCalu0xfwfv6BFquyrTQ8Ad1Kj.jpg'}, {'cast_id': 3, 'character': 'Sayaka', 'credit_id': '52fe4522c3a368484e04a665', 'gender': 1, 'id': 20330, 'name': 'Yuriko Ishida', 'order': 1, 'profile_path': '/ntaS0ZnY7Z3523R1ov6BsrjdVyc.jpg'}, {'cast_id': 4, 'character': 'Takashi Iguchi', 'credit_id': '52fe4522c3a368484e04a669', 'gender': 0, 'id': 13277, 'name': 'Gadarukanaru Taka', 'order': 2, 'profile_path': None}, {'cast_id': 5, 'character': 'Kazuo', 'credit_id': '52fe4522c3a368484e04a66d', 'gender': 0, 'id': 20344, 'name': 'Dankan', 'order': 3, 'profile_path': None}, {'cast_id': 6, 'character': 'Akira', 'credit_id': '52fe4522c3a368484e04a671', 'gender': 0, 'id': 20341, 'name': 'Makoto Ashikawa', 'order': 4, 'profile_path': '/lOcFd8QSCXMHP727uPRQX2oFZ2b.jpg'}, {'cast_id': 7, 'character': 'Otomo, the gang boss', 'credit_id': '52fe4522c3a368484e04a675', 'gender': 2, 'id': 96637, 'name': 'Hisashi Igawa', 'order': 5, 'profile_path': '/ua7RA1qr9LD9k0vOGgNwwhYhkIr.jpg'}, {'cast_id': 8, 'character': 'Minamizaka', 'credit_id': '52fe4522c3a368484e04a679', 'gender': 0, 'id': 96638, 'name': 'Johnny Okura', 'order': 6, 'profile_path': '/8PgP7xp8FqHB57LqTYtmgX9BawO.jpg'}, {'cast_id': 9, 'character': 'Tamagi', 'credit_id': '52fe4522c3a368484e04a67d', 'gender': 0, 'id': 96639, 'name': 'Katsuo Tokashiki', 'order': 7, 'profile_path': None}, {'cast_id': 10, 'character': 'Uehara', 'credit_id': '52fe4522c3a368484e04a681', 'gender': 2, 'id': 3317, 'name': 'Takeshi Kitano', 'order': 8, 'profile_path': '/xkXZ7HC8uyhu5MtNnbdP8mhdiFN.jpg'}, {'cast_id': 11, 'character': 'Kanai', 'credit_id': '52fe4522c3a368484e04a685', 'gender': 0, 'id': 68989, 'name': 'Hitoshi Ozawa', 'order': 9, 'profile_path': None}]	[{'credit_id': '52fe4522c3a368484e04a68b', 'department': 'Writing', 'gender': 2, 'id': 3317, 'job': 'Screenplay', 'name': 'Takeshi Kitano', 'profile_path': '/xkXZ7HC8uyhu5MtNnbdP8mhdiFN.jpg'}, {'credit_id': '52fe4522c3a368484e04a65d', 'department': 'Directing', 'gender': 2, 'id': 3317, 'job': 'Director', 'name': 'Takeshi Kitano', 'profile_path': '/xkXZ7HC8uyhu5MtNnbdP8mhdiFN.jpg'}, {'credit_id': '52fe4522c3a368484e04a69d', 'department': 'Crew', 'gender': 0, 'id': 4998, 'job': 'Cinematography', 'name': 'Katsumi Yanagijima', 'profile_path': None}, {'credit_id': '52fe4522c3a368484e04a691', 'department': 'Production', 'gender': 0, 'id': 31077, 'job': 'Producer', 'name': 'Toshio Nabeshima', 'profile_path': None}, {'credit_id': '52fe4522c3a368484e04a697', 'department': 'Production', 'gender': 0, 'id': 73143, 'job': 'Executive Producer', 'name': 'Kazuyoshi Okuyama', 'profile_path': None}, {'credit_id': '52fe4522c3a368484e04a6b5', 'department': 'Crew', 'gender': 0, 'id': 146656, 'job': 'Stand In', 'name': 'Makoto Tsugawa', 'profile_path': None}, {'credit_id': '52fe4522c3a368484e04a6af', 'department': 'Lighting', 'gender': 0, 'id': 146663, 'job': 'Gaffer', 'name': 'Hitoshi Takaya', 'profile_path': None}, {'credit_id': '52fe4522c3a368484e04a6a3', 'department': 'Editing', 'gender': 0, 'id': 554163, 'job': 'Editor', 'name': 'Toshio Taniguchi', 'profile_path': None}, {'credit_id': '52fe4522c3a368484e04a6a9', 'department': 'Crew', 'gender': 0, 'id': 1108681, 'job': 'Special Effects', 'name': 'Kikuo Notomi', 'profile_path': None}, {'credit_id': '52fe4522c3a368484e04a6bb', 'department': 'Costume & Make-Up', 'gender': 0, 'id': 1108686, 'job': 'Makeup Artist', 'name': 'Yoshie Hamada', 'profile_path': None}]	Takeshi Kitano	/name/nm0001429/	Takeshi Kitano, \nYûrei Yanagi, \nYuriko Ishida, \nTaka Guadalcanal	/name/nm0001429/,/name/nm0648764/,/name/nm0410942/,/name/nm0407276/	left_only
49865	ＳＭガールズセイバーマリオネットＲ	NaN	NaN	NaN	[{'id': 878, 'name': 'Science Fiction'}, {'id': 35, 'name': 'Comedy'}]	30.0	Jr., the heir of Romana and his battle sabers Cherry and Lime, who have girl circuits are enjoying their peaceful life in Romana. Suddenly, the evil Star-Face and his sexadolls attack Romana in order to take over so Star-Face can become the next High Official. In order to truly become the next High Official and ruler of Romana, he must first eliminate Jr. This begins a battle for, not only Jr.'s life, but for all of Romana.	NaN	ja	0.0	ｓｍガールズセイバーマリオネットｒ	[{'iso_3166_1': 'JP', 'name': 'Japan'}]	tt3422000	[{'name': 'ANIMATE', 'id': 13064}, {'name': 'Zero G Room', 'id': 53165}]	1995-05-21	1995.0	[{'cast_id': 21, 'character': 'Cherry (voice)', 'credit_id': '57800ae3c3a3682e16001b45', 'gender': 1, 'id': 555550, 'name': 'Yuri Shiratori', 'order': 0, 'profile_path': '/obLK8jNQo7McZ9CRvmcEk1SS5DQ.jpg'}, {'cast_id': 1, 'character': 'Lime', 'credit_id': '55504011c3a36852210019cf', 'gender': 1, 'id': 40325, 'name': 'Megumi Hayashibara', 'order': 1, 'profile_path': '/aYeXdOAsEh2xItISYDefJfvcdA.jpg'}, {'cast_id': 0, 'character': 'Bloodberry', 'credit_id': '55503fff92514105cf000799', 'gender': 1, 'id': 143502, 'name': 'Akiko Hiramatsu', 'order': 2, 'profile_path': '/v0F4QOBvuwoAbQKxdBVBBai4hEb.jpg'}, {'cast_id': 2, 'character': 'Junior', 'credit_id': '555040209251411b8b000619', 'gender': 0, 'id': 1221862, 'name': 'Yuka Imai', 'order': 3, 'profile_path': '/rs2zugdmDqNvqmeitF4oWzSayoC.jpg'}, {'cast_id': 4, 'character': 'Face', 'credit_id': '55504041c3a3682254005e31', 'gender': 0, 'id': 122726, 'name': 'Hikaru Midorikawa', 'order': 4, 'profile_path': '/67LlDJlFDeIrZlI4o6IM23fG7Tr.jpg'}, {'cast_id': 5, 'character': 'Brid', 'credit_id': '555040519251416a93000a07', 'gender': 0, 'id': 101913, 'name': 'Kikuko Inoue', 'order': 5, 'profile_path': '/5L2IMLJIN7XynIn5tVr80dcaKNG.jpg'}, {'cast_id': 6, 'character': 'Edge', 'credit_id': '555040629251413eee000cd8', 'gender': 1, 'id': 555104, 'name': 'Urara Takano', 'order': 6, 'profile_path': '/8t7c1CCvjK9f3TMvoZKNM4mIQpq.jpg'}, {'cast_id': 7, 'character': 'Kyanny', 'credit_id': '55504072c3a36818700068cc', 'gender': 0, 'id': 112138, 'name': 'Yuko Mizutani', 'order': 7, 'profile_path': '/n7zoT3w5pkorKvIBrFBhqjAamW2.jpg'}, {'cast_id': 8, 'character': 'Villey', 'credit_id': '55504081c3a3687953003b88', 'gender': 0, 'id': 229191, 'name': 'Banjou Ginga', 'order': 8, 'profile_path': None}, {'cast_id': 10, 'character': 'sexadoll A(Act 2)', 'credit_id': '555040a4c3a36818700068d8', 'gender': 1, 'id': 1241505, 'name': 'Kujira', 'order': 10, 'profile_path': '/akW1HjQxB8qrceyok2WzxOEIpyn.jpg'}, {'cast_id': 11, 'character': 'Patrol Saber(Act 1)', 'credit_id': '555040b4c3a3687f63003c10', 'gender': 1, 'id': 554874, 'name': 'Miyuki Matsushita', 'order': 11, 'profile_path': None}, {'cast_id': 12, 'character': 'Sunchest(Act 1)', 'credit_id': '555040c4c3a3687f63003c16', 'gender': 2, 'id': 62318, 'name': "Shin'ichirou Miki", 'order': 12, 'profile_path': '/7eU3YGGkQsTuiQU3xvSRA6nNZdC.jpg'}, {'cast_id': 13, 'character': 'sex doll B(Act 2)', 'credit_id': '555040d5c3a3686d06001071', 'gender': 1, 'id': 553925, 'name': 'Tomoko Nakajima', 'order': 13, 'profile_path': '/nO2YfEcGEuNoFW6wpF4N1gUgc1v.jpg'}, {'cast_id': 14, 'character': 'Announcer(Act 1)', 'credit_id': '555040e6c3a3687f63003c1d', 'gender': 2, 'id': 112278, 'name': 'Wataru Takagi', 'order': 14, 'profile_path': '/j0mQoLTEwzWYoJTsPtl9X25V43R.jpg'}, {'cast_id': 15, 'character': 'Bureaucrat(Act 2)', 'credit_id': '555040f7c3a3685bbf000c30', 'gender': 2, 'id': 553282, 'name': 'Yasunori Matsumoto', 'order': 15, 'profile_path': '/wStHWJbhaoN1uNIPmRUH32ry6co.jpg'}, {'cast_id': 16, 'character': 'Adali(Act 2) Lun(Act 1)', 'credit_id': '555041079251411b8b000642', 'gender': 1, 'id': 83768, 'name': 'Yuko Miyamura', 'order': 16, 'profile_path': '/aXRz2l0YzDtiuJSTkKJPaeKdLNN.jpg'}, {'cast_id': 22, 'character': 'Old Guy (voice)', 'credit_id': '58070d4292514170b7018529', 'gender': 2, 'id': 142704, 'name': 'Kenichi Ogata', 'order': 17, 'profile_path': '/wkwtFf4yGpErhxt5ira7nEi0trt.jpg'}]	[{'credit_id': '55504222c3a3685bbf000c5c', 'department': 'Writing', 'gender': 2, 'id': 77923, 'job': 'Storyboard', 'name': 'Kazuya Tsurumaki', 'profile_path': '/5yc1Q20SafIjC9gxjz1OhDQbzye.jpg'}, {'credit_id': '555041229251416a93000a28', 'department': 'Directing', 'gender': 0, 'id': 1249974, 'job': 'Director', 'name': 'Koji Masunari', 'profile_path': None}, {'credit_id': '5550413c9251413eee000cf2', 'department': 'Crew', 'gender': 0, 'id': 1249974, 'job': 'Script', 'name': 'Koji Masunari', 'profile_path': None}, {'credit_id': '5550423c9251413f32000da6', 'department': 'Sound', 'gender': 0, 'id': 1451781, 'job': 'Music', 'name': 'Toshiyuki Omori', 'profile_path': None}]	NaN	NaN	NaN	NaN	left_only

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